About this role
Company Description
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.
Job Description
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