AIP Innovation Engineer - iDEA

AIP Innovation Engineer – iDEA by Lear

Location:

Southfield, MI, US

Job Function:
Information Technology

Employment Type:

Salary

Lear is a global Tier 1 automotive supplier of Seating and E-Systems. Through IDEA by Lear (Innovation, Digital, Engineering & Automation), we're executing a multiyear digital transformation powered by Palantir Foundry and Palantir AIP to unify data, accelerate automation, and scale AI driven decisioning across our business and plants worldwide. We're building an elite team to turn this investment into impact.

As an AIP Innovation Engineer, you'll be on the front line—accelerating our AI adoption by designing and delivering AI automation solutions that plug into our Foundry ecosystem (Foundry AIP) and deliver measurable outcomes.

The AIP Innovation Engineer is a hands on builder and visionary to demonstrate "what is possible" with AIP/AI/Agentic AI across existing and new Foundry solutions. You'll design, implement, and operationalize LLM/agent workflows, integrate internal and external data sources, and partner with Ontology Leads to shape data for maximum automation. This is not a "model only" role; it's an end to end engineering role that spans data ingestion → semantic grounding → agent design → apps/APIs → productionization—with intelligent monitoring, observability, and guardrails baked in.

• Agentic AI & AIP Enablement
• Data & Integration Engineering
• Ontology Driven AI
• Reliability, Data Health & Guardrails
• Productionization & Performance
• Solution Delivery & Stakeholder Collaboration

4+ years building production data/AI solutions (startup or enterprise); demonstrated hands on ownership from ingestion to deployment. Strong experience with LLM/agentic systems: prompt design, tool/function calling, retrieval/grounding, safety policies, and evaluation. Proficiency with at least two of:
Python, Type Script/JavaScript, PySpark; comfort with APIs, microservices, and event driven patterns. Experience with Palantir Foundry and/or AIP (Ontology, pipelines, transformations, apps, agents). If not Palantir, deep experience with adjacent stacks (e.g., Lang Chain/Lang Graph/CrewAI/Auto Gen/Semantic Kernel; vector DBs; cloud AI services) and the ability to ramp to Palantir quickly. Practical Data Quality & Observability experience (contracts, schema checks, lineage, alerts, evals) and a bias toward operational excellence.

Comfortable working without a mature EDW—able to roll up sleeves to wrangle messy data, define interim schemas, and harden pipelines.

Prior work integrating AI into manufacturing/industrial contexts (e.g., mapping to ISA‑95 hierarchies, OEE, quality/NCR, routings, genealogy). LLMOps/MLOps experience (MLflow, model registries, eval pipelines, CI/CD for prompts/agents). Cloud experience (Azure/AWS) for scaling inference, storage, and data movement. Familiarity with secure by design patterns: identity, access, secrets, PII handling, audit logging.

Ship 1–2 targeted AIP agent MVPs grounded on existing ontology objects and iterate using eval feedback. Build or harden ingestion → delivery paths for a high value use case, including intelligent data health monitoring and simple cost/perf dashboards. Partner with Ontology Leads to propose reusable object patterns that enable at least two additional AI use cases.

Time to first value for new AI use cases (from scoped to MVP in weeks, not months). Reuse rate of agent tools, connectors, and ontology objects across teams. Data health SLOs met (freshness, schema stability, error budget) and measurable improvements in LLM/agent eval metrics. Production reliability (MTTR, incident count) and cost/performance improvements over baselines.

It's not a pure research or model‑only role—you'll build end‑to‑end systems where models, data, and software meet. You'll help shape Lear's enterprise ontology to amplify automation and speed across solutions. You'll be part of a high‑performing team with executive sponsorship and a multi‑year commitment to Foundry + AIP.