Job Opportunities API

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. YOUR ROLE IN OUR MISSION: As a Product Reliability Engineer, you will build the validation and quality systems that ensure our products work reliably in complex technical environments, including on-prem and customer-managed deployments. You will work closely with engineering and product teams to understand key workflows, identify failure modes, and turn manual validation into automated systems. This role is ideal for someone who understands product quality and reliability deeply, writes production-quality code fluently, and treats modern AI and agentic tools as the primary way the work gets done. This is a hands-on IC role and our first dedicated reliability hire: you will do the validation work yourself while building the systems that eliminate it. You may spend one day building automated test coverage for a critical user workflow, another day using agents to accelerate regression testing, and another day partnering with engineers to debug and operationalize reliability improvements. We're hiring someone who can bring structure, automation, and strong engineering judgment to the way Normal validates and ships software. RESPONSIBILITIES: - Validation Systems: Build automated validation and reliability systems across key product workflows. - AI-Native Tooling: Use LLMs and agents as core tooling for testing, debugging, validation, and quality workflows. - Automation: Translate repetitive manual validation workflows into scalable automation; develop tooling that improves regression testing, release validation, and issue reproduction. - Reliability Partnership: Partner with product engineers to understand user workflows, define expected behavior, and identify reliability gaps. - Failure Analysis: Investigate bugs, reproduce issues, document failure patterns, and convert recurring problems into durable automation. - Cross-Team Quality: Collaborate with engineers across frontend, backend, ML, and infrastructure to improve product reliability. WHAT MAKES YOU A GREAT FIT: - Fluent in using LLMs and agentic tools as primary tooling in your daily engineering work, including generating tests, reproducing bugs, and automating validation - Experience in QA automation, reliability engineering, test engineering, software engineering, or a closely related role - Strong scripting and automation skills, with the ability to write clean, practical code to automate repetitive or complex workflows - Experience building automated tests, validation frameworks, regression suites, or internal reliability tooling - Experience with CI/CD, release validation, observability, or production reliability workflows - Strong debugging instincts and attention to detail, able to turn ambiguous issues into clear technical problems with intuition for how complex systems fail in practice BONUS POINTS FOR: - Experience testing developer tools, infrastructure products, EDA tools, ML systems, or other complex technical software - Experience using LLMs or agents to generate tests, validate outputs, reproduce bugs, or automate QA workflows - Experience working in a startup or small engine