EDA Simulation Automation Engineer

Role overview

EDA Simulation Automation Engineer at onsemi India

Role Summary We are looking for a hands-on EDA Simulation Automation Engineer to join our AI-native product development team at onsemi.

Responsibilities

• You will also identify where commercial EDA tool licensing or concurrency limits constrain simulation throughput, and research, evaluate, or build custom and open-source alternatives that can be integrated into the platform's automation pipeline.
• Support AI agent tool-calling integrations for EDA tools by defining safe, well-scoped automation boundaries, required parameters, and expected outputs for each tool.
• Review and sign off on automated simulation results and generated KPI/compliance reports against domain expectations before release certification.
• Collaborate with model-generation and layout/GDS teams to ensure electrical and thermal models feeding simulations remain accurate and traceable.

Required qualifications

• Provide simulation domain expertise during project scoping, test-suite definition, and requirements-to-KPI mapping discussions. #LI-VS1 3 to 5 years of hands-on experience running simulations for power semiconductor or power module design, with direct, practical use of at least two or three of: Ansys Discovery, Q3D, HFSS, IcePak, Mechanical, Cadence Virtuoso, Spectre, Calibre, SIMetrix/SIMPLIS, or PLECS.

Employment details

• Location: Bangalore [Karnataka] [India]

Additional role details

• The role sits at the intersection of power semiconductor module simulation and engineering automation: you bring deep, practical experience running electrical, thermal, and mechanical simulations across industry-standard EDA tools, and you partner with our software and AI agent engineering team to codify that expertise into repeatable, automatable workflows.
• Today, every design cycle waits on a few subject-matter experts to configure tools, run simulations, and extract KPIs by hand.
• Your job is to break that bottleneck by defining standardized inputs, outputs, and KPI extraction logic that our platform can orchestrate and scale across engineers, teams, and products.
• Success Expectations You would become the platform's trusted domain authority for simulation configuration, execution, and KPI extraction — defining clear, documented automation contracts for each supported EDA tool, validating that automated and agent-driven simulation runs match expert-derived results, and steadily expanding the set of tools and KPIs the platform can orchestrate without manual SME intervention on every cycle. #LI-VS1 Own hands-on simulation execution for power module characterization across electrical, thermal, and mechanical domains using tools such as Ansys Discovery, Q3D, HFSS, IcePak, Mechanical, OptiSLang, Cadence Virtuoso, Spectre, Calibre (DRC/LVS/PEX), SIMetrix/SIMPLIS, and PLECS.
• Define and validate KPI extraction logic from raw simulation outputs, including loop inductance, on-resistance (RDS(on)), switching energy, junction temperature (Tj,max), thermal resistance (Rth), and power-cycling lifetime.
• Design standardized, parameterized test-bench definitions and post-processing rules that convert raw tool outputs into compliance-ready KPI values.
• Document tool-specific configuration, input/output file schemas, and scripting hooks (Python, tool APIs, batch/command-line modes) so engineering can automate configuration, dispatch, and result ingestion for each tool.
• Partner with software and SDET engineers to build and validate simulation regression pipelines, ensuring automated or agent-driven runs reproduce trusted, manually-derived golden results.
• Capture and formalize simulation best practices, known-good configurations, and troubleshooting knowledge that today lives only with individual SMEs, so it can be reused across teams and products.
• Research, evaluate, and prototype custom or open-source alternatives to commercial EDA tools where per-seat licensing or concurrency limits throttle agentic, parallelized simulation throughput, and propose where such alternatives can safely substitute or supplement licensed tools.
• Solid understanding of power module electrical, thermal, and mechanical characterization and the KPIs engineers derive from each (parasitics, loop inductance, resistance, thermal resistance, junction temperature, lifetime/reliability metrics).
• Practical experience configuring simulation inputs (parameters, test benches, boundary conditions) and interpreting/post-processing raw simulation outputs into engineering KPIs.
• Scripting ability in Python sufficient to automate tool configuration, batch execution, and output parsing.
• Working knowledge of GDS/layout-based design flows and how layout, parasitic extraction, and model generation feed downstream simulation.
• Ability to translate tribal SME knowledge into clear, documented, repeatable procedures that a software or AI agent engineer can implement without deep tool expertise.
• Comfort researching and evaluating open-source, custom-built, or alternative simulation/extraction methods to work around commercial tool licensing or concurrency bottlenecks.
• Strong attention to detail in validating automated results against known-good manual runs, with a rigorous approach to signing off on release-quality simulation data.
• Good collaboration and communication skills to work closely with software engineers, SDETs, and AI coding agents on a shared automation roadmap. #LI-VS1