Palantir Forward Deployed AI Engineer / AIP Engineer
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- Model the operational domain first, then ground AI in an enterprise source of truth
- Build agents that safely reason over enterprise logic, tools and operational actions
- Ship evaluated, governed agent systems and own operational outcomes with customers
Benchmark: Palantir Forward Deployed AI Engineer + AIP / Foundry / Ontology agent-platform signals (current Sep 2026). Market refresh: customer GenAI strategy + delivery; Ontology modeling; AIP / AI FDE; pro-code agents; OSDK; semantic search + OAG; AIP Logic; Palantir MCP + Ontology MCP; controlled actions; AIP Evals; automation; production security, auditability, deployment and measurable operational outcomes.
Who’s Hiring Right Now
US openings posted in the last 7 days at Palantir — this role’s own benchmark employers — refreshed daily, as of 2026-11-01. Pulled directly from each company’s public job board; not exhaustive, and postings close fast — worth confirming the details on the employer’s own site before applying.
Enrichment
Model the operational domain first, then ground AI in an enterprise source of truth
Ontology modeling + operational application foundations
Coverage: Foundry Ontology / Objects / Links / Actions / Interfaces / Workshop / OSDK / Domain Modeling
Semantic search, enterprise grounding + OAG
Coverage: Semantic Search / Embeddings / RAG / Ontology-Augmented Generation / Data Tools / Citations + Grounding
Build agents that safely reason over enterprise logic, tools and operational actions
AI FDE, pro-code agents + MCP/OSDK tool architecture
Coverage: AI FDE / Pro-Code Agents / Palantir MCP / Ontology MCP / OSDK / External Agent SDKs / Scoped Permissions
Logic, actions + human-agent process orchestration
Coverage: AIP Logic / Ontology Actions / Tool Use / Human Approval / Automate / Process Mining / Operational Workflows
Ship evaluated, governed agent systems and own operational outcomes with customers
AIP Evals, safe iteration + production guardrails
Coverage: AIP Evals / AI FDE Eval Loop / Test Suites / Variance / Permissions / Auditability / Branch-Aware Debugging
Optimization, scale + forward-deployed outcome ownership
Coverage: Decision Optimization / Human-Agent Teams / Foundry Production / Reliability / Adoption / Mission Outcomes / Executive Delivery
Role-Readiness Proof / Capstone
Run a forward-deployed AI engagement for a real or simulated customer. Translate a high-stakes operational problem into an Ontology with explicit objects, links, actions and permissions; ingest and ground enterprise data; build semantic/OAG retrieval; implement an AIP or pro-code agent that uses OSDK plus Palantir MCP or Ontology MCP, including at least one controlled write/action and human approval; encode one decision or automation workflow in AIP Logic; create AIP Evals for quality, tool selection and failure modes; ship a Workshop/OSDK experience, instrument usage and operational KPIs, rehearse an incident/rollback, and present an executive outcome readout plus next-phase roadmap.
Proof Rubric
- Show a traceable customer problem and outcome metric
- strong Ontology/domain modeling
- governed data and action access
- grounded retrieval and citations
- correct OSDK/MCP contracts
- explicit human-agent control boundaries
- reliable AIP Logic and automation
- meaningful eval suites and regression evidence
- secure permissions and auditability
- production telemetry, failure recovery and deployment discipline
- measurable operational/adoption impact
- crisp stakeholder communication
- and evidence that field learnings changed the product, workflow or platform design