Palantir AI engineers

Overview Job Description: AI Engineer (Palantir Foundry & AIP) Role Overview As an AI Engineer, you will be the architect of our intelligence layer. You won't just be building models in isolation; you will be leveraging Palantir Foundry and AIP to create integrated, "human-in-the-loop" AI applications. Your goal is to transform static data assets into dynamic, agentic workflows that solve complex operational challenges. Key Responsibilities * AIP Logic & Tooling: Design and implement AIP Logic functions and integrate LLMs (Large Language Models) into Foundry workflows. * Ontology Architecture: Map complex business processes into the Foundry Ontology, ensuring AI models have a structured, semantic understanding of the organization. * Pipeline Development: Build robust data pipelines using PySpark and Foundry Data Connection to feed high-quality data into AI features. * Prompt Engineering & Orchestration: Develop and refine prompts and use AIP Assist or Automate to create autonomous agents and decision-support tools. * Application Building: Use Workshop and Slate to build intuitive front-end interfaces where end-users can interact with AI insights. * Governance & Ethics: Implement rigorous testing, versioning, and "checks and balances" within the AIP framework to ensure AI outputs are safe, reliable, and explainable. Technical Qualifications | Category | Requirements | |---|---| | Palantir Core | Proficiency in Foundry Ontology, Workshop, Contour, and Pipeline Builder. | | AI/ML Skills | Deep understanding of AIP Logic, LLM orchestration (RAG), and prompt engineering. | | Languages | Expert-level Python and PySpark. Familiarity with TypeScript/SQL is a plus. | | Data Engineering | Experience with data modeling, ETL/ELT, and managing large-scale datasets. | | DevOps/Mojo | Knowledge of Foundry’s modeling objective (Mojo) and CI/CD for ML models. | Preferred Experience * Experience building Agentic Workflows (AI that can take actions, not just answer questions). * A background in a highly regulated industry (Finance, Healthcare, Defense) where data privacy and security are paramount. * Palantir certifications (e.g., Foundry Data Engineer or Foundry Public Sector). The Ideal Candidate You are a "full-stack" data thinker. You don't wait for a clean dataset; you go into the Foundry filesystem, find what you need, model it into the Ontology, and wrap an AIP-driven solution around it. You value security-first AI and understand that an LLM is only as good as the data it can access. Responsibilities Job Description: AI Engineer (Palantir Foundry & AIP) Role Overview As an AI Engineer, you will be the architect of our intelligence layer. You won't just be building models in isolation; you will be leveraging Palantir Foundry and AIP to create integrated, "human-in-the-loop" AI applications. Your goal is to transform static data assets into dynamic, agentic workflows that solve complex operational challenges. Key Responsibilities * AIP Logic & Tooling: Design and implement AIP Logic functions and integrate LLMs (Large Language Models) into Foundry workflows. * Ontology Architecture: Map complex business processes into the Foundry Ontology, ensuring AI models have a structured, semantic understanding of the organization. * Pipeline Development: Build robust data pipelines using PySpark and Foundry Data Connection to feed high-quality data into AI features. * Prompt Engineering & Orchestration: Develop and refine prompts and use AIP Assist or Automate to create autonomous agents and decision-support tools. * Application Building: Use Workshop and Slate to build intuitive front-end interfaces where end-users can interact with AI insights. * Governance & Ethics: Implement rigorous testing, versioning, and "checks and balances" within the AIP framework to ensure AI outputs are safe, reliable, and explainable. Technical Qualifications | Category | Requirements | |---|---| | Palantir Core | Proficiency in Foundry Ontology, Workshop, Contour, and Pipeline Builder. | | AI/ML Skills | Deep understanding of AIP Logic, LLM orchestration (RAG), and prompt engineering. | | Languages | Expert-level Python and PySpark. Familiarity with TypeScript/SQL is a plus. | | Data Engineering | Experience with data modeling, ETL/ELT, and managing large-scale datasets. | | DevOps/Mojo | Knowledge of Foundry’s modeling objective (Mojo) and CI/CD for ML models. | Preferred Experience * Experience building Agentic Workflows (AI that can take actions, not just answer questions). * A background in a highly regulated industry (Finance, Healthcare, Defense) where data privacy and security are paramount. * Palantir certifications (e.g., Foundry Data Engineer or Foundry Public Sector). The Ideal Candidate You are a "full-stack" data thinker. You don't wait for a clean dataset; you go into the Foundry filesystem, find what you need, model it into the Ontology, and wrap an AIP-driven solution around it. You value security-first AI and understand that an LLM is only as good as the data it can access. Requirements Job Description: AI Engineer (Palantir Foundry & AIP) Role Overview As an AI Engineer, you will be the architect of our intelligence layer. You won't just be building models in isolation; you will be leveraging Palantir Foundry and AIP to create integrated, "human-in-the-loop" AI applications. Your goal is to transform static data assets into dynamic, agentic workflows that solve complex operational challenges. Key Responsibilities * AIP Logic & Tooling: Design and implement AIP Logic functions and integrate LLMs (Large Language Models) into Foundry workflows. * Ontology Architecture: Map complex business processes into the Foundry Ontology, ensuring AI models have a structured, semantic understanding of the organization. * Pipeline Development: Build robust data pipelines using PySpark and Foundry Data Connection to feed high-quality data into AI features. * Prompt Engineering & Orchestration: Develop and refine prompts and use AIP Assist or Automate to create autonomous agents and decision-support tools. * Application Building: Use Workshop and Slate to build intuitive front-end interfaces where end-users can interact with AI insights. * Governance & Ethics: Implement rigorous testing, versioning, and "checks and balances" within the AIP framework to ensure AI outputs are safe, reliable, and explainable. Technical Qualifications | Category | Requirements | |---|---| | Palantir Core | Proficiency in Foundry Ontology, Workshop, Contour, and Pipeline Builder. | | AI/ML Skills | Deep understanding of AIP Logic, LLM orchestration (RAG), and prompt engineering. | | Languages | Expert-level Python and PySpark. Familiarity with TypeScript/SQL is a plus. | | Data Engineering | Experience with data modeling, ETL/ELT, and managing large-scale datasets. | | DevOps/Mojo | Knowledge of Foundry’s modeling objective (Mojo) and CI/CD for ML models. | Preferred Experience * Experience building Agentic Workflows (AI that can take actions, not just answer questions). * A background in a highly regulated industry (Finance, Healthcare, Defense) where data privacy and security are paramount. * Palantir certifications (e.g., Foundry Data Engineer or Foundry Public Sector). The Ideal Candidate You are a "full-stack" data thinker. You don't wait for a clean dataset; you go into the Foundry filesystem, find what you need, model it into the Ontology, and wrap an AIP-driven solution around it. You value security-first AI and understand that an LLM is only as good as the data it can access. Job Description: AI Engineer (Palantir Foundry & AIP) Role Overview As an AI Engineer, you will be the architect of our intelligence layer. You won't just be building models in isolation; you will be leveraging Palantir Foundry and AIP to create integrated, "human-in-the-loop" AI applications. Your goal is to transform static data assets into dynamic, agentic workflows that solve complex operational challenges. Key Responsibilities * AIP Logic & Tooling: Design and implement AIP Logic functions and integrate LLMs (Large Language Models) into Foundry workflows. * Ontology Architecture: Map complex business processes into the Foundry Ontology, ensuring AI models have a structured, semantic understanding of the organization. * Pipeline Development: Build robust data pipelines using PySpark and Foundry Data Connection to feed high-quality data into AI features. * Prompt Engineering & Orchestration: Develop and refine prompts and use AIP Assist or Automate to create autonomous agents and decision-support tools. * Application Building: Use Workshop and Slate to build intuitive front-end interfaces where end-users can interact with AI insights. * Governance & Ethics: Implement rigorous testing, versioning, and "checks and balances" within the AIP framework to ensure AI outputs are safe, reliable, and explainable. Technical Qualifications | Category | Requirements | |---|---| | Palantir Core | Proficiency in Foundry Ontology, Workshop, Contour, and Pipeline Builder. | | AI/ML Skills | Deep understanding of AIP Logic, LLM orchestration (RAG), and prompt engineering. | | Languages | Expert-level Python and PySpark. Familiarity with TypeScript/SQL is a plus. | | Data Engineering | Experience with data modeling, ETL/ELT, and managing large-scale datasets. | | DevOps/Mojo | Knowledge of Foundry's modeling objective (Mojo) and CI/CD for ML models. | Preferred Experience * Experience building Agentic Workflows (AI that can take actions, not just answer questions). * A background in a highly regulated industry (Finance, Healthcare, Defense) where data privacy and security are paramount. * Palantir certifications (e.g., Foundry Data Engineer or Foundry Public Sector). The Ideal Candidate You are a "full-stack" data thinker. You don't wait for a clean dataset; you go into the Foundry filesystem, find what you need, model it into the Ontology, and wrap an AIP-driven solution around it. You value security-first AI and understand that an LLM is only as good as the data it can access. Job Description: AI Engineer (Palantir Foundry & AIP) Role Overview As an AI Engineer, you will be the architect of our intelligence layer. You won't just be building models in isolation; you will be leveraging Palantir Foundry and AIP to create integrated, "human-in-the-loop" AI applications. Your goal is to transform static data assets into dynamic, agentic workflows that solve complex operational challenges. Key Responsibilities * AIP Logic & Tooling: Design and implement AIP Logic functions and integrate LLMs (Large Language Models) into Foundry workflows. * Ontology Architecture: Map complex business processes into the Foundry Ontology, ensuring AI models have a structured, semantic understanding of the organization. * Pipeline Development: Build robust data pipelines using PySpark and Foundry Data Connection to feed high-quality data into AI features. * Prompt Engineering & Orchestration: Develop and refine prompts and use AIP Assist or Automate to create autonomous agents and decision-support tools. * Application Building: Use Workshop and Slate to build intuitive front-end interfaces where end-users can interact with AI insights. * Governance & Ethics: Implement rigorous testing, versioning, and "checks and balances" within the AIP framework to ensure AI outputs are safe, reliable, and explainable. Technical Qualifications | Category | Requirements | |---|---| | Palantir Core | Proficiency in Foundry Ontology, Workshop, Contour, and Pipeline Builder. | | AI/ML Skills | Deep understanding of AIP Logic, LLM orchestration (RAG), and prompt engineering. | | Languages | Expert-level Python and PySpark. Familiarity with TypeScript/SQL is a plus. | | Data Engineering | Experience with data modeling, ETL/ELT, and managing large-scale datasets. | | DevOps/Mojo | Knowledge of Foundry's modeling objective (Mojo) and CI/CD for ML models. | Preferred Experience * Experience building Agentic Workflows (AI that can take actions, not just answer questions). * A background in a highly regulated industry (Finance, Healthcare, Defense) where data privacy and security are paramount. * Palantir certifications (e.g., Foundry Data Engineer or Foundry Public Sector). The Ideal Candidate You are a "full-stack" data thinker. You don't wait for a clean dataset; you go into the Foundry filesystem, find what you need, model it into the Ontology, and wrap an AIP-driven solution around it. You value security-first AI and understand that an LLM is only as good as the data it can access.