Palantir Foundry Engineer

Role & responsibilities

We are looking for strong Palantir Foundry / AIP Engineers who can work across application development, data engineering, Ontology design, and AI workflow implementation.

The ideal candidate should have hands-on experience building end-to-end enterprise solutions - not just Foundry pipelines or dashboards. You should be capable of translating business problems into scalable, data-driven applications and intelligent workflows.

You will work across the complete solution lifecycle : External Data Sources - Data Engineering - Ontology - Business Logic & Actions - Applications - AIP / AI Workflows.

Experience similar to an AI Forward Deployed Engineer (AI FDE), with the ability to understand business requirements and translate them into working technical solutions, is highly desirable.

Key Responsibilities :

• Design, develop, and maintain end-to-end solutions using Palantir Foundry and AIP.

• Integrate data from internal and external enterprise sources and build reliable data pipelines.

• Design and implement business-oriented Ontology models, including object types, properties, relationships, actions, and functions.

• Develop business applications and workflows using Foundry Workshop, Ontology APIs, and related application development tools.

• Build AI-powered workflows, agents, and enterprise applications using Palantir AIP and large language models.

• Implement business logic, automated actions, and human-in-the-loop workflows.

• Collaborate with business stakeholders to understand requirements and convert them into scalable technical solutions.

• Ensure data quality, lineage, governance, access controls, and production reliability.

• Integrate Foundry applications and AI workflows with enterprise systems, APIs, and external tools.

• Troubleshoot, optimise, and continuously improve data pipelines, applications, and AI workflows.

Mandatory Technical Skills :

1. Palantir Foundry - Data Integration & Engineering :

Hands-on experience in several of the following :

• Data Connections and external data source integrations.

• Pipeline Builder and Code Repositories.

• Python and PySpark transformations.

• Dataset modelling and data transformations.

• Data quality, lineage, and dependency management.

• Contour and Quiver for data exploration and analysis.

• Foundry Automate for workflow automation.

Strong traditional data engineering experience is a significant advantage.

2. Palantir Ontology - Critical Requirement :

Strong practical knowledge of Palantir Ontology is essential. Candidates should demonstrate an understanding of :

• Ontology Object Types, Properties, and Relationships / Links.

• Actions, Functions, and Interfaces.

• Mapping datasets and data models into Ontology.

• Building object-backed applications and business workflows.

• Designing Ontology around real-world business concepts rather than simply exposing database tables.

• Using Ontology as the semantic and operational layer connecting data, applications, workflows, and AI.

3. Palantir Application Development :

Experience building applications on top of Foundry data and Ontology, including :

• Foundry Workshop and Ontology-backed applications.

• Actions, Functions, and business workflows.

• Code Repositories and Developer Console.

• React and TypeScript-based application development.

• Custom applications using Ontology APIs.

• Integration with internal and external enterprise systems.

Strong software engineering and application development skills are highly desirable.

4. Palantir AIP / AI Workflows :

Candidates must demonstrate a good understanding of Palantir AIP, with hands-on experience in the following preferred :

• AIP Logic and LLM-powered workflows.

• AI agents and workflow orchestration.

• Using Ontology as context for AI-driven applications.

• Tool calling and function calling.

• AIP applications and AI-driven Actions.

• Human-in-the-loop workflows.

• AI governance, permissions, and access controls.

• MCP (Model Context Protocol).

• Integrating AI workflows with enterprise systems, tools, and external services.

Candidates should understand how to operationalise AI against enterprise data and business processes, beyond basic LLM prompting.

5. Programming & Data Engineering :

High-priority skills :

• Python.

• PySpark.

• SQL.

• Data transformations and modelling.

• ETL / ELT concepts.

• Large-scale data processing.

Additional advantages :

• React, TypeScript, and JavaScript.

• REST APIs and backend application development.

• Cloud platforms.

• Databricks, Apache Spark, or similar data platforms.

Preferred candidate profile

• Strong hands-on experience with Palantir Foundry and Ontology.

• Practical exposure to Palantir AIP and AI workflow implementation.

• A strong foundation in data engineering and software development.

• Ability to work across data pipelines, semantic modelling, application development, and AI integration.

• Experience translating business requirements into production-ready technical solutions.

• Strong analytical, problem-solving, and stakeholder collaboration skills.

• An AI Forward Deployed Engineer mindset, combining technical depth with business problem-solving.

What Makes You a Strong Fit? :

You are a strong fit if you can demonstrate how you have taken a business problem from raw data ingestion through data engineering, Ontology modelling, business logic, application development, and AI-powered workflows. We value engineers who can build complete enterprise solutions rather than specialists limited to a single layer of the Foundry platform.

Interested candidates with hands-on experience in Palantir Foundry, Ontology, and AIP / AI workflows are encouraged to apply.