Software Engineer, Product
Normal Computing
About Normal Computing Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt. We co-design the full stack: AI-native EDA systems in production with the world's largest semiconductor companies, and the advanced ASICs they make possible. Backed by $85M+ from the world's leading deep-tech investors and built by scientists, engineers, and operators from the labs that built modern computing. Normal works as one team across New York, Silicon Valley, London, Copenhagen, and Seoul. We hire people who want the hardest version of their craft, across every discipline, at every seniority. The Role As an AI Product Engineer at Normal, you will build AI-native products and workflows for semiconductor engineers. This role sits at the intersection of product engineering, AI systems, and developer tooling. You'll ship real improvements to hardware teams who want to design and verify chips more efficiently, while pushing the boundaries of what's possible in AI for engineering through innovations in interface and workflow design, data modeling, and harness engineering. What You Will Own
- UX & AX : Architect interfaces and workflows that make highly technical systems intuitive and usable for chip engineers, as well as the agentic system they use.
- Partnership : Partner closely with AI engineers, researchers, hardware engineers, and users to turn ambiguous workflow problems into clear requirements, explicit system behaviors, evaluation criteria, and working product features.
- End to End Product : Understand the user problem and define the workflow through implementation, deployment, evaluation, and iteration across frontend, backend, data, and AI systems.
- Judgment : Design and build product experiences for complex engineering workflows, taking them from initial prototype through the final layers of usability, reliability, performance, and polish required for production adoption.
- Raise the Quality Bar : Identify subtle workflow, UX, and architectural weaknesses that make a system merely functional rather than genuinely effective.
- AI-Native Execution : Use AI systems to accelerate implementation, exploration, testing, and analysis while maintaining clear ownership of requirements, verification, and final quality.
- 5+ years of experience building and shipping full stack products, ideally in fast-moving startup or zero-to-one environments
- Strong proficiency in TypeScript and React, with deep understanding of modern frontend architecture and how web technologies work
- Experience building backend systems in Python, Node.js or other popular languages, with the ability and desire to contribute across the stack
- A high bar for product and engineering quality, with the ability to identify subtle UX regressions, incomplete edge-case handling, and architectural choices that create long-term maintenance costs.
- Effective in ambiguous environments: you proactively reduce uncertainty, identify the decisions that matter, and turn evolving product direction into concrete, testable plans.
- Reliable, resourceful, and execution-oriented: you deliver on commitments, adapt quickly, and maintain a high standard for quality
- Experience building AI-powered products, working with LLMs, or collaborating closely with ML teams
- Meaningful experience working within the semiconductor industry or building software for hardware engineering workflows
- Experience building developer tools, workflow systems, IDE extensions, or highly technical internal or business-facing products
- Familiarity with harness engineering, orchestration systems, or evaluation tooling
- Experience with visual design or building polished, user-centric interfaces
- Able to become productive quickly in unfamiliar technical domains by learning the relevant concepts, vocabulary, constraints, and validation methods without requiring prior mastery of every implementation detail.
- Experience as an engineering manager or owning a product end-to-end.
Vacancy posted 5 hours ago
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