Palantir Senior Developer

Our client is expanding its data and AI engineering capabilities and is seeking multiple Senior Palantir Foundry Developers to support large-scale Palantir Foundry and AIP initiatives. These projects focus on building advanced data platforms, AI-driven workflows, and real-time data pipelines that support enterprise decision-making across the organization.This role is ideal for experienced data engineers who have strong hands-on production experience with Palantir Foundry and are comfortable building scalable data pipelines, AI-enabled workflows, and operational applications within the Foundry ecosystem. The position is based in Atlanta with a hybrid schedule (2–3 days onsite). Initial candidates submitted should be local or willing to work onsite.Key Responsibilities

• Design, develop, and deploy scalable data pipelines using Palantir Foundry
• Build and maintain production data workflows using PySpark and TypeScript
• Develop and manage data ingestion frameworks including batch and real-time pipelines
• Work within Foundry features including Code Repositories, Workbooks, and Scheduling
• Build operational applications and analytics tools using Workshop, Contour, and Quiver
• Develop AI-powered workflows leveraging Palantir AIP (Artificial Intelligence Platform)
• Configure and manage AIP Agents, AIP Logics, and AI-enabled decision workflows
• Implement data connections and integrations with enterprise systems
• Utilize Object Manager and OSDK to manage data objects and application logic
• Manage deployment and DevOps workflows using Packages and Marketplace
• Collaborate with data scientists, engineers, and business stakeholders to deliver production-ready solutionsRequired Qualifications
• 4–7+ years of experience in Data Engineering, Data Platforms, or AI Engineering
• Minimum 3+ years of hands-on Palantir Foundry experience in production environments
• Strong programming experience with PySpark
• Experience building applications or workflows using TypeScript
• Experience working with enterprise-scale data pipelines and large datasets
• Experience with batch processing and real-time data ingestion
• Strong understanding of distributed data systems and data engineering best practices
• Experience deploying production-grade data applications in enterprise environments