AI Workflow Engineer (Silicon Engineering Productivity) - Remote / Telecommute

Job Overview: Requirement/Must Have: • BS/MS in Computer Engineering, Computer Science, Electrical Engineering, or equivalent experience. • Understanding of RTL design, DV, simulation, regression, coverage, or SoC development workflows. • Demonstrated experience building AI applications beyond prompt engineering. • Experience creating at least one production-quality AI agent, AI skill/plugin, workflow automation, MCP-based solution, or agent orchestration system. • Strong Python development experience. • Experience with APIs, automation frameworks, and software integration. • Working knowledge of LLMs, RAG architectures, vector databases, agent frameworks, and prompt/context engineering. • Ability to independently decompose ambiguous problems and deliver working solutions. Responsibilities: • Develop AI agents and skills that automate multi-step engineering workflows. • Build retrieval-augmented generation (RAG) systems for engineering knowledge, specifications, design documentation, test plans, and project data. • Create workflow automations that connect engineering tools, repositories, documentation systems, and reporting environments. • Design and implement copilots, assistants, and agentic workflows for specification analysis, test-plan review, coverage analysis, code review, debug assistance, project tracking, and engineering reporting. • Build proof-of-concept solutions and Experienced them into reusable assets. • Evaluate emerging AI models, frameworks, orchestration techniques, and agent architectures. • Develop metrics and dashboards demonstrating engineering productivity improvements. • Work closely with design, DV, program management, and CAD teams to identify high-value automation opportunities. Nice to Have: • Semiconductor industry experience. • Experience integrating AI solutions with GitHub, Perforce, Confluence, SharePoint, Jira, Teams, or engineering databases. • Experience building AI solutions that operate on proprietary engineering documentation and source repositories. • Familiarity with secure enterprise AI deployments. Skills: • Python. • AI Agents. • RAG architectures. • LLMs. • Vector databases. • Agent frameworks. • Workflow automation. • RTL design. • SoC development. • APIs. Qualification And Education: • BS/MS in Computer Engineering, Computer Science, Electrical Engineering, or equivalent experience.