Top Tech Jobs & Startup Jobs

Build and operate production ML infrastructure to convert prototype models (LLM, NLP, recommendation, forecasting, tabular) into low-latency, reliable services. Own CI/CD, containers, orchestration, inference microservices, feature pipelines, model/feature lifecycle, observability, safety/guardrails, and runtime reliability while collaborating with Applied Sciences and Product.

Own end-to-end quality for enterprise data products: design and implement automated testing for pipelines, transformations, APIs, and platform capabilities; validate data correctness, completeness, consistency, freshness, and lineage; build reconciliation frameworks; define data quality metrics and monitoring; create regression suites and drive root-cause analysis; and design evaluation frameworks and test strategies for AI-powered analytics agent outputs.

Own end-to-end quality for ML models and AI agents: design automated testing and evaluation frameworks, create eval datasets, detect hallucinations and regressions, validate integrations and latency, build regression suites and monitoring, perform root-cause analysis, and use LLMs to generate test cases and synthetic data to accelerate quality engineering.

Design, build, and operate an LLM control plane/gateway and agent runtime for multi‑tenant automotive SaaS. Implement retrieval (graph+vector+keyword), MLOps pipelines, monitoring, safety/PII controls, autoscaling, and tooling so product teams can deploy and govern LLM and classical ML models at scale.

Own and run an LLM control plane/gateway and agent runtime, build unified APIs/SDKs, enforce safety/privacy, enable multi-model retrieval and hybrid search, manage ML training/scoring pipelines, monitor model/data drift, define SLOs and observability, and mentor teams to deploy scalable, cost‑aware AI/ML platform features.

Design, build, and operate Tekion's AI platform: an LLM control plane/gateway, agent runtime and orchestration, retrieval/graph-backed context, MLOps pipelines, monitoring, safety/privacy guardrails, and SDK/APIs to enable multi-tenant, cost‑aware, production AI and classical ML models.

Lead validation and quality engineering for Tekion's Enterprise Data Platform. Design and implement automated tests, reconciliation frameworks, data quality metrics, and regression suites. Validate data correctness, lineage, freshness, and platform capabilities. Define and execute AI/Analytics Agent evaluation strategies, create evaluation datasets, measure accuracy, identify hallucinations, and drive root-cause fixes with engineering teams.

Own end-to-end dealer-facing product and integration for Tekion's GM DRP program. Define roadmaps, integration architecture, data contracts, KPIs, and backlog; troubleshoot APIs and event pipelines; align OEM, dealer success, engineering, and leadership; and drive adoption, compliance, and platform scalability.

Validate and ensure end-to-end data quality for the Enterprise Data Platform by designing and implementing automated test and reconciliation frameworks, monitoring data correctness, completeness, freshness, consistency and lineage, partnering with engineering on platform capabilities, executing regression suites and root-cause analysis, and defining/evaluating test strategies and evaluation datasets for AI-powered analytics features.

Lead multiple engineering teams through design, development, and deployment. Define technical strategy and roadmaps, oversee hiring and resource planning, drive engineering best practices and platform modernization, mentor engineering managers, and collaborate cross-functionally to deliver scalable cloud-native solutions.