Forward Deployed Engineer - Semiconductor
About the team OpenAI’s Forward Deployed Engineering team partners with leading semiconductor companies to deploy production-grade AI systems across chip design, verification, and tooling workflows. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to tra
What this role actually needs.
About the team OpenAI’s Forward Deployed Engineering team partners with leading semiconductor companies to deploy production-grade AI systems across chip design, verification, and tooling workflows. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to tra Responsibilities: - Design and ship production AI systems around models, owning integrations with RTL repositories, verification environments, simulators, and internal tooling. - Lead discovery and scoping from pre-engagement through production rollout, translating ambiguous engineering pain points into hypothesis-driven use cases with measurable outcomes. - Deliver AI-powered verification workflows such as change-aware test selection, directed test generation, and intelligent regression triage, taking them from prototype to daily production use. - Build systems that operate over large, evolving codebases and artifacts (RTL, tests, logs, waveforms, traces), where performance, latency, and failure handling shape architecture. - Define and run evaluation loops that measure model and system quality against workflow-specific benchmarks (e.g., coverage, false positives, debug time, iteration speed). - Own delivery state across multiple workstreams, making trade-offs between scope, speed, and robustness to protect production impact. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Forward Deployed Engineer - Semiconductor role.
- Design and ship production AI systems around models, owning integrations with RTL repositories, verification environments, simulators, and internal tooling.
- Lead discovery and scoping from pre-engagement through production rollout, translating ambiguous engineering pain points into hypothesis-driven use cases with measurable outcomes.
- Deliver AI-powered verification workflows such as change-aware test selection, directed test generation, and intelligent regression triage, taking them from prototype to daily production use.
- Build systems that operate over large, evolving codebases and artifacts (RTL, tests, logs, waveforms, traces), where performance, latency, and failure handling shape architecture.
- Define and run evaluation loops that measure model and system quality against workflow-specific benchmarks (e.g., coverage, false positives, debug time, iteration speed).
- Own delivery state across multiple workstreams, making trade-offs between scope, speed, and robustness to protect production impact.
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Source: jobs.ashbyhq.com · Source ID: 853dcb3e-ef04-45f1-be3a-36752c1bd267 · Confidence: 97/100 · Last checked: May 7, 2026
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