SM
Software Mind
AI Engineer
[OWD] Lead Data & AI Engineer (Palantir Foundry/AIP)
On-siteSeniorAI EngineerJust posted
Role summaryAI-generated
Lead the design and deployment of Palantir Foundry data pipelines and ontology components while integrating LLM-powered workflows with AIP Logic, Automate, and Assist. Guide a team of engineers, translating business requirements into production-ready solutions and managing client-facing technical discussions.
Skills required
About this role
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.
Qualifications
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
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