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 :

Robust 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.

📌 Palantir Foundry Engineer (Hyderabad)
🏢 Tech Vedika Software
📍 Hyderabad