Ontologies & Knowledge Graphs (Agentic AI, Surrogates, Physical AI)

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.

Work arrangement
No