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Cadence Design Systems •

AI Full Stack Engineer, Ontologies & Knowledge Graphs (Agentic AI, Surrogates, Physical AI)

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Summary

Location

pune, India

Work

Full-time

Experience

6+ years

Key Skills
Artificial Intelligence Finite Element Analysis (FEA) Generative AI / LLMs Python
Job Classification
Robotics Software Engineer Robotics Software & AI

About this Job

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

AI Full Stack Engineer, Ontologies & Knowledge Graphs (Agentic AI, Surrogates, Physical AI) —

Exp: 6+yrs

Job Location: Pune

Summary: Makes our simulation products AI-accessible. Our products have rich programmatic surfaces — scripting APIs, file formats, data structures, workflow logic — that are powerful but not designed for AI consumption. This engineer defines the ontology schema that describes those surfaces, builds the knowledge graphs on top of them, and wraps them as structured, typed interfaces that AI agents can discover and invoke.

Responsibilities:

  • Define and maintain ontology schemas describing product capabilities, entities, and relationships
  • Build and maintain knowledge graphs over product documentation, APIs, and simulation data
  • Build structured tool interfaces exposing product capabilities to AI systems
  • Write connectors to product APIs, parsers, and data access layers
  • Implement retrieval and context layers over product knowledge
  • Work with domain engineers to translate simulation workflows into discrete, callable operations
  • Review product ontologies for agentic-readiness across 2–3 products

Skills we need:

  • Strong Python; experience building and consuming REST APIs
  • Familiarity with graph databases and/or ontology/semantic modeling (RDF, OWL, property graphs, or equivalent)
  • Experience with at least one agent framework (LangChain, LangGraph, AutoGen, CrewAI, or similar)
  • Understanding of how LLMs consume context and call tools
  • Comfortable working within unfamiliar or undocumented codebases
  • Systems thinker — able to decompose a complex legacy workflow into discrete, callable steps

Nice to have:

Vector databases; agent-tool interface development; parsing structured file formats; exposure to CAE/FEA/CFD, surrogate modeling, or physical AI.

Deliberately not required: Deep simulation domain knowledge — domain engineers provide that. No PhD or ML research background.

We’re doing work that matters. Help us solve what others can’t.

About the Company

Cadence Design Systems logo

Cadence Design Systems

Public Company
Automotive ManufacturingIndustrial ManufacturingRobotics Software & AI

Cadence is a market leader in AI and digital twins, pioneering the application of computational software to accelerate innovation in the engineering design of silicon to systems. Our design solutions, based on Cadence’s Intelligent System Design™ strategy, are essential for the world’s leading semiconductor and systems companies to build their next-generation products from chips to full electromechanical systems that serve a wide range of markets, including hyperscale computing, mobile communications, automotive, aerospace, industrial, life sciences and robotics. In 2024, Cadence was recognized by the Wall Street Journal as one of the world’s top 100 best-managed companies. Cadence solutions offer limitless opportunities—learn more at www.cadence.com.

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