Title: Senior Agentic AI Engineer (Palantir Foundry and AIP)
Location: Remote
Pay rate: per /hr please mention your expectation.
Target Start Date: ASAP (by October 31)
Type: Contract about 15 months. There will be more work after this.
Interview times for this Wednesday!
Why Work Here
This is a data and AI consultancy of builders, not a slide-deck shop. Engineers embed directly with client teams, ship code alongside them, and are trusted with real ownership from day one. You will be included in decisions, work directly with senior leadership, and never be micromanaged. The firm is an official Claude partner, partners with Databricks, Snowflake, AWS, Google Cloud Platform, and Azure, and builds with modern AI tooling every day. AI is the core of what the firm does, so strong engineers get pulled into new work across the business.
About the Role
We are building a team of senior AI engineers, including one team lead, for a 15-month enterprise AI program with a global client. Working in small, senior pods, you will take agentic AI use cases from first idea to production, building reusable agent skills on Palantir Foundry and AIP, Azure, Databricks, and frontier models from OpenAI and Anthropic. This is a fast build-and-ship environment where your work reaches real users and the capabilities you build compound across multiple business use cases. It rewards engineers who can move quickly, consult directly with demanding stakeholders, and take and give candid feedback.
Responsibilities
- Own agentic AI use cases end to end, from ideation and rapid experimentation through testing and production deployment
- Design and build modular agent skills and tools that combine to support multiple business workflows
- Model and extend the Palantir Foundry Ontology (Object Types, Link Types, Action Types, Interfaces) to ground agents in trusted enterprise data
- Build LLM-driven workflows with AIP Logic, AIP Automate, and AIP Assist, and deploy them within Palantir
- Engineer pipelines for structured and unstructured data that feed agentic applications across Foundry, Azure, and Databricks
- Define semantic layers, ontologies, and context layers that give agents the right business context
- Select, deploy, and cost-optimize models from OpenAI, Anthropic, and other providers, including through Azure AI Foundry and Databricks Genie
- Build and maintain GitHub repositories and automated CI/CD pipelines for secure, repeatable production releases
- Lead discovery sessions with client stakeholders and share Palantir knowledge across your pod
Required Skills
- 7+ years of hands-on experience in AI/ML, data science, or LLM engineering, with production work on cloud platforms
- Has shipped at least one agent or LLM workflow that reached real users or a live production system (prototypes, demos, and hackathon projects alone do not meet this requirement)
- Hands-on experience with Palantir Foundry and AIP, ideally taking a use case end to end on the platform
- Hands-on experience deploying LLMs from OpenAI, Anthropic, or other major providers, with a clear view of model selection, deployment tradeoffs, and cost
- Data engineering experience with structured and unstructured data for AI applications, such as RAG, retrieval, and document processing
- Experience with Azure, including Azure AI Foundry, and/or Databricks, including Databricks Genie
- GitHub and DevOps skills, including building CI/CD pipelines for production deployments
- Strong Python and SQL
- Experience working directly with client stakeholders, and availability for a 15-month engagement
Bonus / Soft Skills
- Depth in Foundry Core: Ontology Manager, Object Types, Link Types, Action Types, Interfaces, Property Sets, Object Explorer, Data Lineage, CBAC, Ontology Linter, and Foundry Marketplace
- Experience with AIP Logic, AIP Automate, and AIP Assist
- Palantir experience from the Army Vantage program or other federal government work
- Palantir certifications
- Experience leading a small engineering team or pod (for the team lead role)
- Experience defining semantic layers, ontologies, or context layers on Azure, AWS, or Google Cloud Platform
- DevSecOps experience: secrets management, security scanning, and policy controls in CI/CD
- Deep experience with Claude and Anthropic tooling
- Experience fine-tuning LLMs
- Retail, Client, or financial services data experience
- Thick skin and comfort with fast, direct feedback, both giving and receiving it
