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Tier-1 brand but highly specialized EDA/GenAI and physical-design skillset reduces applicant pool.
Highly domain-specific EDA and physical-design expertise limits transferability across industries.
Explicit 9–12 years plus mandatory EDA/Physical Design, triage, and GenAI pipeline expertise increases filter strictness.
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Own end-to-end support, triage, and debugging of complex EDA toolchains and AI/GenAI workflows related to Physical Design engineering.
Translate user issues into engineering inputs; enable scalable adoption by onboarding projects and defining test cases and validation strategies.
Measure tool performance via key QoR metrics and integrate tools into continuous automated testing and telemetry pipelines.
9-12 years experience in Applications/Customer Engineering, preferably in Physical Design (PNR/Floor planning).
Strong domain expertise in VLSI/Physical Design/EDA workflows and proven triage/debugging skills in complex software/tool environments.
Proficient in Python, Linux, scripting, and able to independently run and debug end-to-end workflows.
Bachelor's degree in Engineering/Information Systems/Computer Science or related plus 4+ years software engineering experience; alternatively M.Tech/PhD with fewer years as specified; programming experience in C/C++/Java/Python mandatory.
Experienced engineering professional bridging physical design CAD teams and software engineering with deep troubleshooting and system debugging capabilities.
Comfortable working with AI/GenAI agent systems, orchestration pipelines, and managing non-deterministic software behaviors.
Strong analytical and problem decomposition abilities to handle complex multi-tool VLSI workflows and drive user-centric engineering solutions.