Senior Engineering Manager

Role Summary

About Flow

Flow Engineering is an AI-native requirements platform for modern engineering organizations, enabling hardware teams to collaborate with AI agents to design, validate, and evolve complex systems with speed and rigor.

Flow is seeking a senior engineering manager to lead a team building the core of our platform. This is our first dedicated engineering management hire, and you will own delivery for a team of engineers while staying hands on with coding.

You will report to our head of engineering and work closely with product, design, and our forward deployed engineers.

Responsibilities

• Manage and grow a team of engineers, owning onboarding, feedback, and career development.
• Own product execution end to end, from scoping with customers through ship, measure, and iterate.
• Stay technical. Review code, make architecture calls, and pick up meaningful work when a project needs it.
• Help establish engineering best practices
• Work directly with customers. Our users are systems and requirements engineers at hardware companies with a high bar
• Partner with recruiting to build the team
• Help set direction on how AI shows up in the product, working with engineers building agentic workflows and LLM-powered features.

About you

• 8+ years developing production software, including designing, testing, and operating services at scale in a cloud environment.
• 2+ years managing engineers, ideally at an early-stage company or somewhere with little existing process scaffolding.
• Track record shipping software that enterprise customers depend on, with a clear understanding of what that changes about how you build.
• Still hands on with coding
• Direct communicator who is able to give difficult feedback
• Comfortable working in a high-ownership, fast-paced environment where experiments and iteration are the norm.

Requirements

Nice to have

• Background in aerospace, defense, automotive, or another regulated hardware domain.
• Experience with requirements, ALM, PLM, or systems engineering tooling.
• Experience managing teams building LLM-powered or agentic features in production.

Our stack

• TypeScript/Node.js and Python for backend and AI services.
• Modern LLM APIs and orchestration libraries for building agentic workflows.
• Postgres and other managed cloud services for data and state.