AI Platform Engineer, Palantir Foundry

The Foundry AI Platform Engineer is responsible for leading the development, deployment, and ongoing management of data models (ontologies), analytics solutions, and AI-driven applications within the Palantir Foundry platform. This role serves as the primary platform engineer and administrator, ensuring platform stability, performance, and usability while translating business needs into scalable, production-ready data and AI solutions. The role partners closely with Technology and business stakeholders to integrate data, analytics, and AI capabilities into operational workflows that support enterprise decision-making.

Platform & Application Enablement: 

• Design, develop, and optimize ontology‑driven data models within Palantir Foundry that support both operational and analytical use cases.
• Deliver enterprise‑facing applications and workflows that are production‑ready, scalable, and aligned to business objectives.

• Support sustained end‑user engagement by ensuring solutions are intuitive, reliable, and fit for real‑world business use.

   

Palantir Foundry Platform Management

• Partner with Technology teams to support platform performance, stability, and reliability in production environments.
• Assist with monitoring, troubleshooting, and operational support of Foundry‑based applications and workflows.
• Align platform usage with enterprise standards for security, access controls, and data governance.

AI‑Driven Solution Development

• Build and support AI‑enabled applications using Palantir Foundry, Python, PySpark, and TypeScript.
• Develop solutions that integrate data pipelines, analytics, and AI capabilities to support enterprise decision‑making.
• Contribute to AI use cases such as forecasting, performance evaluation, and operational optimization.

Analytics & Business Insight

• Analyze large and complex datasets to identify trends, insights, and opportunities that inform business decisions.
• Apply analytics techniques to improve operational efficiency, performance measurement, and planning processes.

Stakeholder Partnership & Governance

• Collaborate closely with business and shared‑services stakeholders to understand workflows and translate requirements into scalable solutions.
• Promote responsible use of data and AI by adhering to established governance, data quality, security, and compliance standards.
• Contribute to documentation, best practices, and reusable patterns that support platform adoption across the organization.