Business applications that are simple and fun to use? 

We've got that covered!

At Tekion, we are on a mission to build the world's best applications. We aim to deliver solutions that are delightful to use, yet powerful enough to efficiently run global businesses. Starting with automotive retail, we are incorporating cutting-edge technologies to accelerate the transition of complex (and simple) businesses to the cloud and enable seamless consumer experiences.

Our journey to tackle the impossible and build the future has only just begun. For our team of seasoned industry leaders and passionate visionaries, continuously going beyond the expected is the norm. We thrive in a culture where the possibilities to act and make an impact are endless, where the aim is to constantly innovate, grow together and drive the disruption of a lifetime!

Join us, and let us Outpace Possibility together!

tekion

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Why This Role MattersWe're looking for a Data Platform Engineer with deep systems engineering expertise and a passion for building reusable infrastructure. You'll helparchitect and deliver the internal frameworks that power data ingestion, transformation, observability, and self-serve analytics across the company. Your work will be central to enabling scalable, multi-tenant ingestion pipelines (including CDC via Debezium), serving layers built on Trino, and robust tooling that lets teams move fast without compromising on data quality or platformhealth.What Makes This Opportunity UniqueBuild platform tooling for multi-region, multi-tenant data infrastructure using modern open-source and cloud-native technologies.Lead engineering efforts around CDC pipelines using Debezium, enabling reliable change capture from application databases.Shape the developer experience for data engineers, from ingestion to publishing and consumption, with metadata-aware automation.Drive the evolution of data serving infrastructure using Trino and open table formats like Delta Lake or Iceberg.Work at the intersection of data engineering, infrastructure, and platform strategy, directly influencing core architectural decisions.Responsibilities Design and implement foundational frameworks for ingestion, orchestration, schema validation, and metadata management. Build robust, scalable pipelines for Change Data Capture (CDC) using Debezium integrated with Kafka and Spark. Optimize data serving layers powered by Trino, including metadata syncing, security filtering, and performance tuning. Partner with SRE and Infra teams to build autoscaling, self-healing, and cost-optimized Spark jobs on AWS EMR. Implement observability features — logs, metrics, alerts — for critical platform services and data pipelines. Define and enforce standards for schema evolution, lineage tracking, and data governance. Automate platform operations using CI/CD pipelines, metadata-driven configurations, and infrastructure-as-code. Desired Skills &amp; Experience 5-7 years of experience in data platform, infrastructure, or backend systems engineering roles. Strong systems engineering fundamentals — distributed systems, fault tolerance, performance tuning. Expertise in Apache Spark with production experience on AWS EMR. Experience building or managing CDC pipelines using tools like Debezium, Kafka Connect, or custom connectors. Familiarity with streaming systems such as Kafka, Kinesis, or Flink. Experience serving data using Trino or Presto in a multi-tenant environment. Proficiency in Python, Java or Scala, and Unix/Linux systems. Strong understanding of open table formats like Delta Lake or Apache Iceberg. Exposure to infrastructure as code (Terraform, CloudFormation) and CI/CD automation. &nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Senior Software Engineer– Data Platform Engineer

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Why This Role Matters&nbsp; This role powers&nbsp;Tekion’s&nbsp;AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence.&nbsp;You’ll&nbsp;operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes.&nbsp;You’ll&nbsp;also build the resilient control layer&nbsp;-&nbsp;MCP and the LLM Gateway&nbsp;-&nbsp;that enables safe, cost‑efficient, multi‑provider LLM usage. Finally,&nbsp;you’ll&nbsp;define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale.&nbsp;In addition to enabling agentic systems powered by LLMs, this role also drives&nbsp;building&nbsp;the&nbsp;platform&nbsp;for&nbsp;classical ML models driving optimization across dealership operations.&nbsp;&nbsp; &nbsp; What Makes This Opportunity Unique&nbsp; This role offers direct, measurable impact on dealer outcomes and consumer experiences across&nbsp;Tekion’s&nbsp;Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and,&nbsp;quality&nbsp;and&nbsp;cost&nbsp;guardrails.&nbsp;You’ll&nbsp;leverage&nbsp;a rich vertical dataset and domain graph spanning sales, service, parts, F&amp;I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation.&nbsp;You’ll&nbsp;also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.&nbsp;&nbsp;You’ll&nbsp;also&nbsp;maintain&nbsp;and enhance the platform to support classical supervised and unsupervised ML&nbsp;models .&nbsp; Responsibilities&nbsp; Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.&nbsp; Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).&nbsp; Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.&nbsp; Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.&nbsp; Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.&nbsp; Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.&nbsp; Enabling platform components for training and scoring pipelines for classical ML (e.g.,&nbsp;XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.&nbsp; Create components to&nbsp;Monitor&nbsp;model and&nbsp;data drift, retraining and tuning models as needed to&nbsp;maintain&nbsp;accuracy and relevance.&nbsp; Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.&nbsp; Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.&nbsp; Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.&nbsp; Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.&nbsp; Run continuous offline/online evaluations for quality, factuality, bias, and safety&nbsp;for the platform sanity.&nbsp; Define SLOs for latency (p50/p95), uptime, and&nbsp;cost&nbsp;view&nbsp;capabilities; enable autoscaling and spend controls.&nbsp; Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances&nbsp;where needed.&nbsp; Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion&nbsp;MLOps&nbsp;and AI safety best practices.&nbsp; &nbsp; Desired Skills &amp; Experience&nbsp; 5+ - 8+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).&nbsp; Production experience with Python plus one of Java/Scala/Go; microservices and API design.&nbsp; MLOps&nbsp;at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).&nbsp; Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.&nbsp; Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.&nbsp; Built or&nbsp;operated&nbsp;an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit,&nbsp;cost&nbsp;and token accounting.&nbsp; Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.&nbsp; Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph),&nbsp;GraphQL, vector search (e.g.,&nbsp;pgvector/Qdrant/Milvus), hybrid retrieval patterns.&nbsp; Preferred Mindset&nbsp; Platform‑as‑product: obsess over developer experience, paved roads, and clear&nbsp;SLAs.&nbsp; Thinks in systems&nbsp;-&nbsp;observability, fallback, access control are core, not afterthoughts.&nbsp; Passionate about AI&nbsp;-&nbsp;enjoys enabling real-world LLM and agentic use cases.&nbsp; Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.&nbsp; Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.&nbsp; &nbsp; &nbsp;&nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Senior Software Engineer (Machine Learning Platform)

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Why This Role Matters&nbsp; This role powers&nbsp;Tekion’s&nbsp;AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence.&nbsp;You’ll&nbsp;operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes.&nbsp;You’ll&nbsp;also build the resilient control layer&nbsp;-&nbsp;MCP and the LLM Gateway&nbsp;-&nbsp;that enables safe, cost‑efficient, multi‑provider LLM usage. Finally,&nbsp;you’ll&nbsp;define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale.&nbsp;In addition to enabling agentic systems powered by LLMs, this role also drives&nbsp;building&nbsp;the&nbsp;platform&nbsp;for&nbsp;classical ML models driving optimization across dealership operations.&nbsp;&nbsp; &nbsp; What Makes This Opportunity Unique&nbsp; This role offers direct, measurable impact on dealer outcomes and consumer experiences across&nbsp;Tekion’s&nbsp;Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and,&nbsp;quality&nbsp;and&nbsp;cost&nbsp;guardrails.&nbsp;You’ll&nbsp;leverage&nbsp;a rich vertical dataset and domain graph spanning sales, service, parts, F&amp;I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation.&nbsp;You’ll&nbsp;also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.&nbsp;&nbsp;You’ll&nbsp;also&nbsp;maintain&nbsp;and enhance the platform to support classical supervised and unsupervised ML&nbsp;models .&nbsp; Responsibilities&nbsp; Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.&nbsp; Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).&nbsp; Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.&nbsp; Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.&nbsp; Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.&nbsp; Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.&nbsp; Enabling platform components for training and scoring pipelines for classical ML (e.g.,&nbsp;XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.&nbsp; Create components to&nbsp;Monitor&nbsp;model and&nbsp;data drift, retraining and tuning models as needed to&nbsp;maintain&nbsp;accuracy and relevance.&nbsp; Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.&nbsp; Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.&nbsp; Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.&nbsp; Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.&nbsp; Run continuous offline/online evaluations for quality, factuality, bias, and safety&nbsp;for the platform sanity.&nbsp; Define SLOs for latency (p50/p95), uptime, and&nbsp;cost&nbsp;view&nbsp;capabilities; enable autoscaling and spend controls.&nbsp; Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances&nbsp;where needed.&nbsp; Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion&nbsp;MLOps&nbsp;and AI safety best practices.&nbsp; &nbsp; Desired Skills &amp; Experience&nbsp; 12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).&nbsp; Production experience with Python plus one of Java/Scala/Go; microservices and API design.&nbsp; MLOps&nbsp;at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).&nbsp; Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.&nbsp; Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.&nbsp; Built or&nbsp;operated&nbsp;an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit,&nbsp;cost&nbsp;and token accounting.&nbsp; Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.&nbsp; Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph),&nbsp;GraphQL, vector search (e.g.,&nbsp;pgvector/Qdrant/Milvus), hybrid retrieval patterns.&nbsp; Preferred Mindset&nbsp; Platform‑as‑product: obsess over developer experience, paved roads, and clear&nbsp;SLAs.&nbsp; Thinks in systems&nbsp;-&nbsp;observability, fallback, access control are core, not afterthoughts.&nbsp; Passionate about AI&nbsp;-&nbsp;enjoys enabling real-world LLM and agentic use cases.&nbsp; Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.&nbsp; Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.&nbsp; Documentation and teaching: you make complex systems understandable; you uplevel teams.&nbsp; &nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Senior Staff Software Engineer (Machine learning Platform)

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Why This Role Matters&nbsp; This role powers&nbsp;Tekion’s&nbsp;AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence.&nbsp;You’ll&nbsp;operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes.&nbsp;You’ll&nbsp;also build the resilient control layer&nbsp;-&nbsp;MCP and the LLM Gateway&nbsp;-&nbsp;that enables safe, cost‑efficient, multi‑provider LLM usage. Finally,&nbsp;you’ll&nbsp;define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale.&nbsp;In addition to enabling agentic systems powered by LLMs, this role also drives&nbsp;building&nbsp;the&nbsp;platform&nbsp;for&nbsp;classical ML models driving optimization across dealership operations.&nbsp;&nbsp; &nbsp; What Makes This Opportunity Unique&nbsp; This role offers direct, measurable impact on dealer outcomes and consumer experiences across&nbsp;Tekion’s&nbsp;Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and,&nbsp;quality&nbsp;and&nbsp;cost&nbsp;guardrails.&nbsp;You’ll&nbsp;leverage&nbsp;a rich vertical dataset and domain graph spanning sales, service, parts, F&amp;I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation.&nbsp;You’ll&nbsp;also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.&nbsp;&nbsp;You’ll&nbsp;also&nbsp;maintain&nbsp;and enhance the platform to support classical supervised and unsupervised ML&nbsp;models .&nbsp; Responsibilities&nbsp; Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.&nbsp; Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).&nbsp; Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.&nbsp; Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.&nbsp; Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.&nbsp; Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.&nbsp; Enabling platform components for training and scoring pipelines for classical ML (e.g.,&nbsp;XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.&nbsp; Create components to&nbsp;Monitor&nbsp;model and&nbsp;data drift, retraining and tuning models as needed to&nbsp;maintain&nbsp;accuracy and relevance.&nbsp; Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.&nbsp; Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.&nbsp; Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.&nbsp; Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.&nbsp; Run continuous offline/online evaluations for quality, factuality, bias, and safety&nbsp;for the platform sanity.&nbsp; Define SLOs for latency (p50/p95), uptime, and&nbsp;cost&nbsp;view&nbsp;capabilities; enable autoscaling and spend controls.&nbsp; Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances&nbsp;where needed.&nbsp; &nbsp; &nbsp; Desired Skills &amp; Experience&nbsp; 4 - 5+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).&nbsp; Production experience with Python plus one of Java/Scala/Go; microservices and API design.&nbsp; MLOps&nbsp;at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).&nbsp; Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.&nbsp; Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.&nbsp; Built or&nbsp;operated&nbsp;an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit,&nbsp;cost&nbsp;and token accounting.&nbsp; Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.&nbsp; Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph),&nbsp;GraphQL, vector search (e.g.,&nbsp;pgvector/Qdrant/Milvus), hybrid retrieval patterns.&nbsp; Preferred Mindset&nbsp; Platform‑as‑product: obsess over developer experience, paved roads, and clear&nbsp;SLAs.&nbsp; Thinks in systems&nbsp;-&nbsp;observability, fallback, access control are core, not afterthoughts.&nbsp; Passionate about AI&nbsp;-&nbsp;enjoys enabling real-world LLM and agentic use cases.&nbsp; Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.&nbsp; Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.&nbsp; &nbsp;&nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Software Engineer II - (Machine Learning Platform)

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Why This Role MattersWe're looking for a Data Platform Engineer with deep systems engineering expertise and a passion for building reusable infrastructure. You'll helparchitect and deliver the internal frameworks that power data ingestion, transformation, observability, and self-serve analytics across the company. Your work will be central to enabling scalable, multi-tenant ingestion pipelines (including CDC via Debezium), serving layers built on Trino, and robust tooling that lets teams move fast without compromising on data quality or platformhealth.What Makes This Opportunity UniqueBuild platform tooling for multi-region, multi-tenant data infrastructure using modern open-source and cloud-native technologies.Lead engineering efforts around CDC pipelines using Debezium, enabling reliable change capture from application databases.Shape the developer experience for data engineers, from ingestion to publishing and consumption, with metadata-aware automation.Drive the evolution of data serving infrastructure using Trino and open table formats like Delta Lake or Iceberg.Work at the intersection of data engineering, infrastructure, and platform strategy, directly influencing core architectural decisions.Responsibilities Design and implement foundational frameworks for ingestion, orchestration, schema validation, and metadata management. Build robust, scalable pipelines for Change Data Capture (CDC) using Debezium integrated with Kafka and Spark. Develop internal tooling to standardize and accelerate data ingestion, transformation, and publishing workflows. Optimize data serving layers powered by Trino, including metadata syncing, security filtering, and performance tuning. Partner with SRE and Infra teams to build autoscaling, self-healing, and cost-optimized Spark jobs on AWS EMR. Implement observability features — logs, metrics, alerts — for critical platform services and data pipelines. Define and enforce standards for schema evolution, lineage tracking, and data governance. Automate platform operations using CI/CD pipelines, metadata-driven configurations, and infrastructure-as-code. Desired Skills &amp; Experience 7+–12 years of experience in data platform, infrastructure, or backend systems engineering roles. Strong systems engineering fundamentals — distributed systems, fault tolerance, performance tuning. Expertise in Apache Spark with production experience on AWS EMR. Experience building or managing CDC pipelines using tools like Debezium, Kafka Connect, or custom connectors. Familiarity with streaming systems such as Kafka, Kinesis, or Flink. Experience serving data using Trino or Presto in a multi-tenant environment. Proficiency in Python, Java or Scala, and Unix/Linux systems. Strong understanding of open table formats like Delta Lake or Apache Iceberg. Exposure to infrastructure as code (Terraform, CloudFormation) and CI/CD automation. Preferred Mindset Platform-first thinker — designs systems for scale, abstraction, and reusability. Builder's bias — values automation, clean interfaces, and measurable SLAs.Deep collaborator — partners well across Data, Infra, and Engineering teams. Operational discipline — understands the impact of monitoring, logging,and reliability. &nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Staff Software Engineer – Data Platform Engineer

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Senior Software Engineer&nbsp; -&nbsp; Senior Machine Learning Platform Why This Role Matters&nbsp; This role powers&nbsp;Tekion’s&nbsp;AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence.&nbsp;You’ll&nbsp;operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes.&nbsp;You’ll&nbsp;also build the resilient control layer&nbsp;-&nbsp;MCP and the LLM Gateway&nbsp;-&nbsp;that enables safe, cost‑efficient, multi‑provider LLM usage. Finally,&nbsp;you’ll&nbsp;define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale.&nbsp;In addition to enabling agentic systems powered by LLMs, this role also drives&nbsp;building&nbsp;the&nbsp;platform&nbsp;for&nbsp;classical ML models driving optimization across dealership operations.&nbsp;&nbsp; What Makes This Opportunity Unique&nbsp; This role offers direct, measurable impact on dealer outcomes and consumer experiences across&nbsp;Tekion’s&nbsp;Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and,&nbsp;quality&nbsp;and&nbsp;cost&nbsp;guardrails.&nbsp;You’ll&nbsp;leverage&nbsp;a rich vertical dataset and domain graph spanning sales, service, parts, F&amp;I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation.&nbsp;You’ll&nbsp;also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.&nbsp;&nbsp;You’ll&nbsp;also&nbsp;maintain&nbsp;and enhance the platform to support classical supervised and unsupervised ML&nbsp;models .&nbsp; Responsibilities&nbsp; Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking.&nbsp; Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics).&nbsp; Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction.&nbsp; Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning.&nbsp; Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval.&nbsp; Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows.&nbsp; Enabling platform components for training and scoring pipelines for classical ML (e.g.,&nbsp;XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging.&nbsp; Create components to&nbsp;Monitor&nbsp;model and&nbsp;data drift, retraining and tuning models as needed to&nbsp;maintain&nbsp;accuracy and relevance.&nbsp; Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems.&nbsp; Evolve the domain graph and entity resolution; build reliable data ingestion pipelines.&nbsp; Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage.&nbsp; Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost.&nbsp; Run continuous offline/online evaluations for quality, factuality, bias, and safety&nbsp;for the platform sanity.&nbsp; Define SLOs for latency (p50/p95), uptime, and&nbsp;cost&nbsp;view&nbsp;capabilities; enable autoscaling and spend controls.&nbsp; Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances&nbsp;where needed.&nbsp; Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion&nbsp;MLOps&nbsp;and AI safety best practices.&nbsp; Desired Skills &amp; Experience&nbsp; 5 - 7 years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems).&nbsp; Production experience with Python plus one of Java/Scala/Go; microservices and API design.&nbsp; MLOps&nbsp;at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka).&nbsp; Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS.&nbsp; Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows.&nbsp; Built or&nbsp;operated&nbsp;an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit,&nbsp;cost&nbsp;and token accounting.&nbsp; Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry.&nbsp; Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph),&nbsp;GraphQL, vector search (e.g.,&nbsp;pgvector/Qdrant/Milvus), hybrid retrieval patterns.&nbsp; Preferred Mindset&nbsp; Platform‑as‑product: obsess over developer experience, paved roads, and clear&nbsp;SLAs.&nbsp; Thinks in systems&nbsp;-&nbsp;observability, fallback, access control are core, not afterthoughts.&nbsp; Passionate about AI&nbsp;-&nbsp;enjoys enabling real-world LLM and agentic use cases.&nbsp; Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation.&nbsp; Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience.&nbsp; Documentation and teaching: you make complex systems understandable; you uplevel teams.&nbsp; &nbsp;&nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Senior Software Engineer -  (Machine learning Platform)

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Job Description &nbsp; Key Responsibilities &nbsp; Skills and Experience &nbsp; Preferred Skills &nbsp; Perks and Benefits&nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Lead Software Engineer

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Role OverviewWe are seeking a senior, technically strong Product Manager to own platform capabilities across one of our&nbsp;engineering Scrum teams while driving customer-facing outcomes and continuous improvement. This role&nbsp;requires close collaboration with Engineering, AI, and platform teams, along with hands-on understanding of&nbsp;event-driven systems, agentic AI integration, scalable service design, and data-driven product development. Key Responsibilities• Own the product backlog for a Scrum team — writing clear, actionable user stories, acceptance criteria, and&nbsp;feature specifications aligned with business goals.• Partner closely with Engineering and AI teams to deliver high-quality solutions across Java microservices,&nbsp;Kafka event pipelines, and agentic platform integrations.• Collaborate with platform and infrastructure teams to ensure seamless integrations, well-defined data&nbsp;contracts, and API alignment.• Track success metrics, adoption, and outcomes — iterating rapidly based on data and field feedback.• Author Intent definitions, Skill specifications, and Policy configurations for the agentic platform layer (PRDas-Code approach).• Design and maintain golden dataset scenarios used to validate intelligent capabilities before release.• Drive change management and adoption of new features, tools, and platform capabilities.• Build and maintain automations using workflow tools (Zapier or equivalent) to streamline internal processes.• Demonstrate strong understanding of RESTful APIs, webhooks, and authentication mechanisms;&nbsp;troubleshoot integration issues hands-on.• Work with data teams to define schemas, reporting views, and analytics instrumentation.• Facilitate prioritization discussions, manage stakeholder expectations, and communicate trade-offs clearly&nbsp;across Engineering, Design, and Leadership. Skills &amp; Qualifications• 6+ years of Product Management experience, preferably in platform, data-driven, or AI-enabled products.• Strong experience collaborating with engineering teams on technical products — comfortable reading&nbsp;system designs, API specs, and data models.• Proven analytical and problem-solving skills with a data-driven mindset; experience defining and tracking&nbsp;product KPIs.• Hands-on experience with RESTful APIs, webhooks, and system integrations (ERP, CRM, data platforms,&nbsp;or cloud services).• Familiarity with AI systems, LLM-based tools, and agentic AI patterns (intent routing, skill/policy design,&nbsp;MCP tools).• Experience designing scalable, maintainable solution architectures in collaboration with engineering.• Excellent verbal and written communication skills; strong stakeholder management across technical and&nbsp;non-technical audiences.• Structured problem-solving and critical thinking; ability to navigate complex system trade-offs.• Bachelor's or Master's degree in IT, Computer Science, Business Administration, or a related field. Good to Have• Experience authoring PRD-as-Code artifacts: Intent definitions, Skill specs, Policy configurations.• Background in marketing technology, CDP, or customer data platforms.• Experience with LMS platforms and user enablement programs.• Prior experience in automotive retail or dealer technology. Perks &amp; Benefits• Competitive compensation and generous stock options.• Medical insurance coverage.• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies&nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

Staff Product Manager

About Tekion: Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.Summary: ​Lead the strategy, development, and execution of key product initiatives that drive customer value and support business objectives. Collaborate cross-functionally to deliver impactful product solutions, ensuring alignment with market needs and company goals. ​ Duties &amp; Responsibilities: • ​Develop and execute product strategies and roadmaps for assigned product lines or platforms. • ​Collaborate with engineering, design, marketing, and go-to-market teams to define and launch new features or products. • ​Engage with customers, sales, and customer success teams to gather feedback, validate concepts, and ensure value delivery. • ​Analyze market trends, competitive landscape, and usage data to inform prioritization and product evolution. • ​Lead cross-functional initiatives, managing dependencies, risks, and communication across teams. • ​Mentor other product managers and contribute to organizational frameworks, tools, and practices. • ​Define success metrics and ensure product outcomes are measurable and aligned to strategic objectives. ​ Job Complexity: Manages complex product areas with significant business impact and cross-functional coordination. Leads initiatives from concept through launch and post-release optimization. ​ Required Supervision: Operates independently with strategic input from senior leadership. Drives product direction and execution with broad authority. ​ Expertise: Deep product management expertise with a strong understanding of user needs, market dynamics, and technical feasibility. Viewed as a thought leader within the product organization. ​ Qualifications: • ​8–10 years of experience in product management, including ownership of major product lines or features • ​Strong background in SaaS, cloud platforms, or enterprise technology products • ​Bachelor’s degree in Business, Computer Science, Engineering, or related field; advanced degree preferred • ​Proven success in developing and scaling products in cross-functional environments • ​Strong analytical, leadership, and communication skills • ​Experience with Agile methodologies, product lifecycle tools, and data-driven decision-making&nbsp; Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.&nbsp; For more information on our privacy practices, please refer to our Applicant Privacy Notice here.

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