Lead Software Engineer: AI for Hardware Verification

Cadence Design Systems•San Jose, CA

4d•$119,000 - $221,000•Onsite

About The Position

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology. Cadence Design Systems Inc. is looking for a motivated Lead Software Engineer to work with us in San Jose, California. The HSV Software team builds AI-enabled software products that support emulation and prototyping platforms, helping customers accelerate design bring-up, debug, verification, and validation workflows. Working at Cadence is very dynamic, fast-paced, and integrated with other teams all around the world.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience; typically 4+ years with a Bachelor’s, 2+ years with a Master’s, or PhD-level preparation in related software development.
Strong Python skills and software engineering fundamentals, including APIs, testing, debugging, maintainability, Unix/Linux environments, and distributed development workflows.
Hands-on experience building AI-enabled applications, agentic workflows, or automation services using LLM APIs, open-source models, enterprise AI platforms, and orchestration tools such as LangGraph, LangChain, AutoGen, CrewAI, or similar frameworks.
Understanding of modern RAG and agentic AI patterns, including retrieval, chunking, embeddings, vector or hybrid search, reranking, tool calling, workflow orchestration, human-in-the-loop review, and traceability.
Ability to evaluate, secure, and debug AI product behavior using golden datasets, regression tests, hallucination checks, prompt and retrieval analysis, observability traces, quality metrics, and responsible AI practices.

Nice To Haves

Experience developing software using version control systems and modern CI/CD practices.
Experience with other programming languages such as C++, Tcl, or JavaScript/TypeScript.
Knowledge or experience with design verification, emulation, prototyping, or hardware-assisted debug workflows.
Knowledge or experience with EDA and VLSI design, including Verilog, SystemVerilog, or VHDL.
Exposure to practical AI application security, such as prompt-injection awareness, safe tool integration, access control, input/output validation, or secure handling of design data.

Responsibilities

Design and develop AI-enabled software components for emulation and prototyping workflows, balancing reliability, maintainability, security, latency, cost, and integration with existing product architecture.
Build LLM-based agents, RAG workflows, and automation services that improve design bring-up, verification, debug, and validation while recommending product enhancements beyond defect fixes.
Apply secure and responsible AI practices, including data protection, access control, prompt-injection awareness, safe tool use, auditability, and careful handling of sensitive design data.
Create and execute testing, evaluation, and observability workflows for assigned AI product areas, covering regression tests, retrieval quality, model-output review, tracing, and failure analysis.
Serve as a technical resource for peers and less-experienced engineers, collaborating with internal partners, senior individual contributors, and managers to deliver high-quality AI-enabled software.