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

*Note that this is NOT a new grad role! This role is for candidates with 0-2 YOE and can start full time right away.

Flow is hiring early career software engineers to help build AI-powered capabilities that let teams author, review, and manage requirements more effectively. You will work alongside experienced engineers on agentic systems engineer and agentic domain engineer workflows, bringing AI into the center of how teams reason about their systems.

This is a role for people early in their careers who are ready for an unusual amount of responsibility and autonomy. You will ship code to production in your first weeks, work directly with customers building rockets, satellites, and aircraft, and learn full-stack and AI engineering from people who have done it before.

What you'll do

• Ship AI-powered features such as assisted requirement drafting, consistency checks, impact analysis, and intelligent suggestions for systems and domain engineers.

• Contribute to agentic workflows that help engineers explore designs, simulate changes, and validate requirements.

• Work across the stack, from backend services and APIs to the UI, so you own complete features rather than isolated pieces.

• Help build the surrounding infrastructure: data pipelines, evaluation harnesses, prompt and model management, and observability.

• Talk to customers, watch how they actually use what you built, and iterate quickly.

• Learn the domain. Requirements engineering for hardware is deep, unfamiliar to most software engineers, and the reason our product is hard to copy.

About you

• You have less than two years of engineering experience. You have solid fundamentals in data structures, algorithms, and distributed systems, with a customer-minded, pragmatic approach to solving problems.

• Strong programming fundamentals and demonstrated ability to build real software, whether through internships, research, open source, or personal projects you can walk us through.

• Some exposure to modern LLM tooling, whether that is coursework, a side project, or an internship. You do not need production AI experience, but you should be genuinely interested in building with these systems.

• Clear communication. You can explain a technical decision and say when you are stuck.

• Comfortable with ambiguity and eager to work in a fast-moving environment where the roadmap changes and experiments are the norm.

Our stack (AI-leaning)

• TypeScript/Node.js and Python for AI and backend services.

• Modern LLM APIs and orchestration libraries for building agentic workflows.

• Postgres and other managed cloud services for data and state.