Director of Engineering - Applied AI

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.

About the role

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.

What you'll do

• 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.

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.