AI Full Stack Engineer, Ontologies & Knowledge Graphs

Cadence is a pivotal leader in electronic design, building upon more than 30 years of computational software expertise. The company applies its underlying Intelligent System Design strategy to deliver software, hardware and IP that turn design concepts into reality. Cadence customers are the world’s most innovative companies, delivering extraordinary electronic products from chips to boards to systems for the most dynamic market applications including consumer, hyperscale computing, 5G communications, automotive, aerospace industrial and health. The Cadence Advantage • The opportunity to work on cutting-edge technology in an environment that encourages you to be creative, innovative, and to make an impact. • Cadence’s employee-friendly policies focus on the physical and mental well-being of employees, career development, providing opportunities for learning, and celebrating success in recognition of specific needs of the employees. • The unique “One Cadence – One Team” culture promotes collaboration within and across teams to ensure customer success. • ·Multiple avenues of learning and development available for employees to explore as per their specific requirement and interests • You get to work with a diverse team of passionate, dedicated, and talented individuals who go above and beyond for our customers, our communities, and each other—every day. Experience: 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.

: • 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