We are an Artificial Intelligence (AI) focused product engineering company, providing our customers in healthcare, retail & e-commerce, manufacturing and hospitality sectors with cutting edge products & solutions, harnessing Big Data Analytics, Vision Analytics, and IoT.

Ever since our inception in March 2010, Tech Vedika has been

• Great Place To Work Certified™(Feb 2025- Feb 2026) Organization 
• Top 50 I Mid-Size India’s Best Workplaces for Women 2022 !
• Top 10 Most Disruptive Face & Image Recognition Solution Providers’2020 – Analytics Insights
• Top 10 Healthcare Analytics Solution Providers’ 2019- Healthcare Outlook Magazine
• Top 20 most amazing AWS Service Providers – CIO Review India 2018

We strive for simple, elegant tech solutions to perform complex tasks. As a scalable technology partner, we enable organisations to improve operational efficiency and unleash new business potential.

We are looking for a Palantir Foundry  with 3–4 years of experience in data engineering and hands-on experience with the Palantir Foundry platform. The candidate will be responsible for building data pipelines, integrating data sources, transforming data, and supporting data-driven applications.

We are looking for strong Palantir Foundry / AIP engineers who can work across Application Development, Data Engineering, Ontology and AI.

The ideal candidate should not be limited to building Foundry pipelines or dashboards. We are looking for someone who understands how to take a business problem from:

External/Data Sources → Data Engineering → Ontology → Business Logic & Actions → Applications → AIP/AI Workflows

Experience resembling an AI Forward Deployed Engineer (AI FDE) is highly desirable.

1. Palantir Foundry – Core Skills

Profiles should demonstrate hands-on experience across several of the following areas:

Data Integration & Engineering

• Data Connections / external source integrations
• Pipeline Builder
• Code Repositories
• Python / PySpark transformations
• Dataset modelling and transformations
• Data quality, lineage and dependency management
• Contour analysis
• Quiver analysis
• Foundry Automate

Candidates with strong traditional Data Engineering experience in addition to Palantir should receive additional preference.

2. Ontology – Critical Skill

Strong Ontology knowledge is one of the most important screening criteria.

Look for candidates who understand:

• Ontology Object Types
• Properties
• Relationships / Links
• Actions
• Functions
• Interfaces
• Object-backed applications
• Mapping datasets/data models into Ontology
• Designing Ontology around business concepts rather than simply exposing database tables

The candidate should understand how Ontology acts as the business/semantic layer connecting data, applications, workflows and AI.

A candidate who has extensive Foundry experience but little understanding of Ontology should not automatically be considered a strong Palantir profile.

3. Palantir Application Development

We want candidates who can build applications on top of the data and Ontology.

Look for:

• Workshop
• Application development using Ontology
• Actions and workflows
• Functions developed through Code Repositories
• Developer Console
• React / TypeScript application development
• Building custom applications using Ontology APIs
• Integration of applications with external/internal enterprise systems

Strong general software engineering or application-development experience is a significant advantage.

4. AIP / AI Capabilities

Candidates should have a good understanding of Palantir AIP and preferably hands-on experience with:

• AIP Logic
• LLM-powered workflows
• Agents / AI workflows
• Using Ontology as context for AI
• Tool/function calling
• AIP applications
• AI-driven Actions
• Human-in-the-loop workflows
• AI governance and access controls
• MCP / Model Context Protocol
• Connecting AI workflows with external systems and tools

We prefer candidates who understand how AI is operationalized against enterprise data and business processes, rather than candidates whose AI knowledge is limited to prompting an LLM.

5. Programming & Data Engineering

Strong programming ability is expected.

High Priority

• Python
• PySpark
• SQL
• Data transformations
• Data modelling
• ETL/ELT concepts
• Large-scale data processing

Additional Advantage

• React
• TypeScript / JavaScript
• REST APIs
• Backend/application development
• Cloud platforms
• Databricks / Spark or similar data platforms

A strong Data Engineering background is a definite plus.

Preferred Candidate Profile

The strongest candidates will have a combination of three areas:

Application Engineering + Data Engineering + AI Engineering

For example:

Data Engineering
→ Connections → Pipeline Builder → PySpark/Python → Data Modelling → Data Quality

Palantir Semantic & Operational Layer
→ Ontology → Objects → Relationships → Actions → Functions → Automate

Application & AI Layer
→ Workshop / Developer Console → React Applications → AIP Logic → Agents → MCP / External Tools

Candidates who can comfortably work across these layers should be prioritized.

Screening Priority

When reviewing profiles, prioritize approximately in this order:

1. Strong Palantir Foundry hands-on experience
2. Strong Ontology understanding
3. Python / PySpark and Data Engineering
4. AIP / AIP Logic / AI workflows
5. Actions, Functions and Code Repositories
6. Pipeline Builder and Data Connections
7. Workshop / application development
8. Developer Console + React/TypeScript
9. Automate
10. Contour / Quiver
11. MCP / external AI/tool integrations

Do not reject an otherwise excellent candidate simply because they haven't used every Palantir application. We are primarily looking for breadth of architecture understanding combined with depth in several areas.

Profiles to Avoid

Be cautious with candidates whose Palantir experience is predominantly:

• Contour/dashboard/report development
• Basic Pipeline Builder usage only
• SQL transformations without broader engineering experience
• Foundry administration/support
• Data ingestion without Ontology experience
• Workshop configuration without application-development fundamentals
• Generic GenAI experience with very little Palantir AIP exposure

These candidates may have Palantir exposure but may not fit the engineering capability we are looking for.

Ideal Summary

The ideal candidate should be capable of saying:

“I can connect enterprise data into Foundry, engineer and transform it using Python/PySpark and Pipeline Builder, model the business domain through Ontology, expose business operations through Actions and Functions, build applications using Workshop or React/Developer Console, and use AIP Logic/AI agents to create intelligent workflows that operate securely against enterprise data and systems.”

At Tech Vedika, we are looking for talented individuals who want to work with driven people. Attain success while working on interesting projects with a culturally diverse group of individuals.

Perks & Benefits of joining TechVedika:

• Growth driven - an opportunity to learn new skills, and certifications sponsored by the company
• Group Insurance
  • Health Insurance (Including spouse and children)
  • Accidental Life Insurance
  • Group Life Insurance
  • Parental Health Insurance (Optional)
• Meal Vouchers 
• Learning Aids
• Work on projects that have a huge impact - work with clients all over the world.
• Latest tools and technology - always driven by the latest, most efficient ways of working
• Process-driven, quality-oriented work

If you want an exciting and dynamic career with unlimited growth potential, then Tech Vedika is the place for you!