[OWD] Lead Data & AI Engineer (Palantir Foundry/AIP)

About the role

We're putting together a senior team for a global consulting client building and deploying enterprise AI solutions at a fast pace. You'll take business problems from idea to production on Palantir Foundry and AIP, combining hands-on development with technical leadership. You'll guide solution design, work directly with client stakeholders, and help other engineers become productive on the platform.

What you'll do

• Build and manage Foundry data pipelines, ontology components, and applications
• Design semantic and context layers with Palantir's ontology: Object, Link, and Action Types, Interfaces, Property Sets
• Build LLM-powered workflows with AIP Logic, AIP Automate, and AIP Assist
• Take agentic AI use cases from prototype to production: build, test, deploy, monitor
• Serve as the team’s Palantir lead, remaining hands-on while guiding solution design, reviewing code, coaching engineers, and resolving technical blockers.
• Own technical delivery of assigned solutions, translating business requirements into clear implementation plans and guiding work through production deployment.
• Lead technical discussions with client stakeholders, explaining design decisions, trade-offs, dependencies, and delivery risks.

What we're looking for

• Hands-on Palantir Foundry and/or AIP experience on real client or production projects
• Experience developing agentic or GenAI applications is strongly preferred.
• Strong software engineering and problem-solving skills
• Experience integrating AI with enterprise data sources, APIs, and business systems
• Solid data engineering background across structured and unstructured data
• Comfortable with fast delivery cycles and requirements that change
• Strong English and clear communication with both technical and business people
• Able to work EST business hours

Nice to have

• Solutions deployed to production inside Palantir
• Ontology Linter, Data Lineage, CBAC, Foundry Marketplace
• Semantic layers, ontologies, or knowledge graphs (Azure, AWS, GCP, Palantir, or Databricks)
• Azure, Azure AI Foundry, Databricks / Genie
• CI/CD with GitHub, DevOps / DevSecOps tooling
• Experience deploying models from OpenAI, Anthropic, or other LLM providers, including model selection and cost optimization
• Experience building reusable agent skills, tools, or components that support multiple use cases