Product Manager

Job Title

Product Manager

Role Summary

Early-career product manager working with the Product Lead and engineering to build AI systems and an autoresearch platform for the ASIC team. Accountable for scoping work, delivering incremental milestones toward tapeout, and turning prototypes into reliable tools used by chip designers.

Experience Level

Entry-level / Early-career - 1–3 years of relevant experience.

Responsibilities

You will define, prototype, and deliver tooling and workflows that accelerate chip research and design. Work includes writing specs, building prototypes, and collaborating with engineers and chip architects.

• Investigate ASIC team workflows, prioritize opportunities, and decide what AI tooling to build.
• Write requirements, user journeys, and successful acceptance criteria for engineering teams.
• Prototype solutions (code or UI) when that communicates progress faster than documents.
• Work with engineers to productionize prototypes and ensure reliability for the ASIC team.
• Ship small code and UI changes: open PRs, fix bugs, learn from reviews, and iterate.
• Collaborate with chip architects and verification teams to scope automation and experiments.

Requirements

Concise list of must-have and nice-to-have qualifications.

• Must-have: 1–3 years in product management, engineering, research, technical program management, or a similar technical role.
• Must-have: A demonstrated project or idea you initiated and delivered to production or a usable prototype.
• Must-have: Regular use of coding agents (e.g., Claude Code, Codex, Cursor) as part of your workflow.
• Must-have: Experience building or evaluating LLM-powered products.
• Must-have: Clear written and verbal communication and comfort working with ambiguous, underspecified problems.
• Must-have: Genuine interest in chip design and ASIC workflows.
• Nice-to-have: Coursework, research, or internship experience in chip architectures, digital design, verification, or hardware performance modeling.
• Nice-to-have: Exposure to SystemVerilog.
• Nice-to-have: Familiarity with LLM inference mechanisms.

Education Requirements

Bachelor's degree in Computer Science, Electrical Engineering, Physics, Mathematics, or a similar field - or equivalent self-taught or practical experience.

About the Company

Company: Normal Computing

Headquarters: New York, NY, USA

Normal Computing develops software and hardware solutions for the semiconductor and AI infrastructure industries, specializing in ASICs for image and video diffusion inference and AI accelerators. The company focuses on architecture and microarchitecture of compute blocks, PE array design, ISA co-design, and FPGA prototyping.