[OWD] 数据与AI工程师（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