AIP Innovation Engineer iDEA by Lear

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AIP INNOVATION ENGINEER iDEA by Lear

SOUTHFIELD MI WORLD HQ (HYRBID)

About Lear and IDEA by Lear

Lear is a global Tier 1 automotive supplier of Seating and E-Systems. Through IDEA by Lear (Innovation Digital Engineering & Automation) were 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.

Were building an elite team to turn this investment into impact. As an AIP Innovation Engineer youll be on the front lineaccelerating our AI adoption by designing and delivering AI automation solutions that plug into our Foundry ecosystem (Foundry AIP) and deliver measurable outcomes.

Position Overview

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. Youll 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; its an end to end engineering role that spans data ingestion semantic grounding agent design apps/APIs productionizationwith intelligent monitoring observability and guardrails baked in.

We prefer Palantir experience (Foundry AIP features like AI FDE and AI Pilot) but will consider strong hands on candidates from adjacent toolchains who can quickly ramp.

Key Responsibilities

Agentic AI & AIP Enablement

• Design and implement AIP agents and LLM backed workflows (prompt flows tools skills policies) that are grounded in Foundry Ontology objects and feature sets.
• Leverage and stay current on Palantirs platform innovations (e.g. AI FDE AI Pilot) bringing forward the right capabilities at the right time.

Data & Integration Engineering

• Identify opportunities via hands-on data work and analysis to drive necessary harmonization/transforms and semantic grounding to support AI/ LLM-based solutions.
• Identify internal and external integrations (partner data supplier feeds SaaS apps) with appropriate security throttling and resilience patterns to bring the right data together securely to leverage AI.

Ontology Driven AI

• Partner with Ontology Leaders to propose and refine ontology objects relationships and reusable semantics that unlock automation and cross use case reuse.
• Influence data shaping required for RAG/grounding action execution reasoning chains and multiagent handoffs.

Reliability Data Health & Guardrails

• Collaborate with Data Quality Lead for intelligent monitoring: data quality checks freshness schema drift lineage latency SLOs evals for LLM output quality red team prompts and safety guardrails.
• Establish evaluation harnesses (offline/online) for agent workflows and prompts; track regression metrics and cost/performance KPIs.

Productionization & Performance

• Build CI/CD pipelines IaC where applicable and observability (logs traces metrics) for AIP agents to ensure AIP agents and Foundry applications operate reliably at scale and can be quickly diagnosed tuned and improved.

Solution Delivery & Stakeholder Collaboration

• Work closely with product owners plant operations quality supply chain and finance to scope high value use cases; rapidly deliver MVPs and iterate to scale.
• Provide clear technical documentation runbooks and handoffs to operations teams.

Required Qualifications

• 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 TypeScript/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. LangChain/LangGraph/CrewAI/AutoGen/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 EDWable to roll up sleeves to wrangle messy data define interim schemas and harden pipelines.

Preferred Qualifications

• Prior work integrating AI into manufacturing/industrial contexts (e.g. mapping to ISA95 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.

What Youll Do in Your First 90 Days

• Ship 12 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.

How Well Measure Success

• 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.

Why This Role is Different

• Its not a pure research or modelonly roleyoull build endtoend systems where models data and software meet.
• Youll help shape Lears enterprise ontology to amplify automation and speed across solutions.
• Youll be part of a highperforming team with executive sponsorship and a multiyear commitment to Foundry AIP.

Nice to Have Experience (Translatable if not Palantir)

• Built agentic AI systems using LangChain LangGraph CrewAI AutoGen Semantic Kernel.
• Implemented RAG with hybrid retrieval adaptive chunking and domainspecific guardrails.
• Designed distributed finetuning (e.g. QLoRA instruction tuning) and stood up LLMOps/MLOps pipelines (MLflow K8s SageMaker Ray).
• Delivered document intelligence (multimodal parsing extraction validation) and operational AI (recommendation anomaly detection forecasting).

Lear Corporation is an Equal Opportunity Employer committed to a diverse workplace.

Applicants must submit their resume for consideration using our applicant tracking system. Due to the high volume of applications received only candidates selected for interviews will be contacted. Candidates must be legally authorized to work in the United States without sponsorship. Unsolicited resumes from search firms or employment agencies or similar will not be paid a fee and will become the property of Lear Corporation.