Product Reliability Engineer

Stack

Responsibilities

• ▹Build automated validation and reliability systems across key product workflows
• ▹Use LLMs and agents as core tooling for testing, debugging, and validation workflows
• ▹Translate repetitive manual validation workflows into scalable automation
• ▹Develop tooling that improves regression testing, release validation, and issue reproduction
• ▹Partner with product engineers to understand user workflows and identify reliability gaps
• ▹Investigate bugs, reproduce issues, document failure patterns, and convert recurring problems into durable automation
• ▹Collaborate with engineers across frontend, backend, ML, and infrastructure to improve product reliability

Requirements

• ▹Fluent in using LLMs and agentic tools as primary tooling in daily engineering work, including generating tests and reproducing bugs
• ▹Experience in QA automation, reliability engineering, test engineering, software engineering, or a related role
• ▹Strong software engineering skills; writes, reviews, and debugs real code daily
• ▹Experience building automated tests, validation frameworks, regression suites, or internal reliability tooling
• ▹Experience validating non-deterministic or LLM-powered systems: evals, golden sets, quality regression detection
• ▹Working knowledge of how web systems fit together (HTTP, proxies, services, deployments) and comfort with logs and metrics
• ▹Experience with CI/CD, release validation, observability, or production reliability workflows
• ▹Strong debugging instincts and attention to detail

Nice to have

• ▹Experience testing developer tools, infrastructure products, EDA tools, or ML systems
• ▹Experience with browser automation and E2E frameworks (e.g. Playwright)
• ▹Experience working in a startup or small engineering team where ownership spans multiple areas

Soft skills

About the company

Normal Computing builds foundational software and hardware that help move technology forward, supporting the semiconductor industry, critical AI infrastructure, and the broader systems that power our world. The team works as one across New York, San Francisco, Copenhagen, Seoul, and London.