Senior Software Engineer (AI for RTL Design & Formal Verification)

• Design, develop, and deploy AI applications using LLMs, agentic frameworks, and related technologies to support RTL, physical and analog design, static/lint checking, and formal verification flows
• Build infrastructure to deploy LLM-powered engineering assistants and multi-turn dialogue systems that help designers and verification engineers debug faster and close coverage sooner
• Develop agentic AI solutions for tasks such as RTL rule and lint checking, RTL optimization, bug triage, formal proof convergence, and static verification report analysis; fine-tune and integrate these solutions with existing CAD/EDA flows
• Build and maintain design databases and dashboards that combine agentic and deterministic retrieval to surface relevant engineering data and speed up design closure
• Collaborate closely with RTL design, DV, formal verification, and CAD/EDA teams to understand pain points and translate them into AI-assisted tooling

Benefits

• Flexible time off in the US
• Parental leave
• 401K
• Retirement and pension plans
• Competitive medical, dental and vision plans

• Proficiency in Python for rapid prototyping, with strong fundamentals in data structures, algorithms, and software engineering practices
• Experience with LLMs, including fine-tuning, building multi-agent systems, RAG pipelines, and vector databases
• 4-10 years of industry experience in software engineering, with direct exposure to RTL design, static/lint verification, or formal verification methodologies
• A proactive, self-directed approach to problem-solving and comfort operating with ambiguity
• Bachelor’s, Master’s degree in Electrical Engineering, Computer Science/Engineering, or equivalent experience
• Familiarity with RTL design languages (Verilog/SystemVerilog) and formal/static verification tools (e.g., JasperGold, VC Formal, or similar) is strongly preferred
• Strong analytical, communication, and interpersonal skills, with a proven ability to work effectively in a fast-paced, cross-functional startup environment
• Direct experience applying AI/ML techniques to EDA or CAD flow problems
• Proficiency in modern software engineering practices, including version control, testing, and CI/CD
• Experience with formal property verification, assertion-based verification (SVA), or static timing/lint tools
• A track record of learning across disparate domains (AI/ML and hardware design) and combining them into novel engineering solutions