Senior Software Engineer

Flow Engineering; San Francisco (CA); On-site; USD 190,000 - 280,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Flexible time off

Meaningful equity

Job summary

Flow Engineering in San Francisco is seeking a Full Stack Senior Software Engineer to develop AI-powered features that enhance requirement management. You will work at the intersection of AI, product, and engineering, designing workflows that optimize how teams manage their requirements. Ideal candidates should have over 5 years of experience in production software and be familiar with modern LLMs. The compensation range is $190K - $280K, complemented by comprehensive health coverage and flexible time off.

Qualifications

• 5+ years developing production software, especially in a cloud environment.
• Hands-on experience with LLM providers and relevant tooling.
• Familiarity with prompt design and evaluation methods.

Responsibilities

• Design and ship AI-powered features for requirement management.
• Build agentic workflows for systems engineers.
• Integrate language models and optimize them for production.

Skills

Production software development

Experience with LLM providers

Cloud environment services

Prompt design expertise

Tradeoff reasoning in models

Fast-paced work adaptability

Tools

TypeScript

Node.js

Python

Postgres

Job description

Overview

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 full stack senior software engineers to build AI-powered capabilities that help teams author, review, and manage requirements more effectively. You will work on agentic systems engineer and agentic domain engineer workflows—bringing AI into the center of how teams reason about their systems.

This role sits at the intersection of AI, product, and full-stack engineering: you will take ideas from prototype all the way to stable, observable features in production.

What You’ll Do

• Design and ship AI-powered features such as assisted requirement drafting, consistency checks, impact analysis, and intelligent suggestions for systems and domain engineers.
• Build agentic workflows that help “agentic systems engineers” and “agentic domain engineers” explore designs, simulate changes, and validate requirements.
• Evaluate and integrate language models and related tooling, optimizing for reliability, latency, cost, and debuggability in production.
• Build and maintain the surrounding infrastructure: data pipelines, evaluation harnesses, prompt and model management, observability, and safety/guardrails.
• Work across the stack—from backend integrations and APIs to simple UI hooks—to deliver complete AI features, not just model endpoints.
• Partner with product and customers to identify high-value workflows, run experiments, and iterate quickly based on usage.

About You

• 5+ years developing production software, including designing, testing, and operating services at scale in a cloud environment.
• Hands-on experience with modern LLM providers and tooling (e.g., OpenAI, Anthropic, Hugging Face, vector stores, RAG patterns).
• Familiarity with prompt design, retrieval-augmented systems, evaluation methods, and safety/guardrail approaches.
• Ability to reason about tradeoffs between different models, architectures, and deployment patterns and make pragmatic decisions.
• Comfortable working in a high-ownership, fast-paced environment where experiments and iteration 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.

How We Work & Values

• Speed over everything: prototype AI workflows quickly, then harden what works.
• Own, downscope, ship, iterate: one clear owner per feature, from prototype to production.
• Fundamentals done well: evaluation, observability, and safety are part of the first version, not an afterthought.
• Competitive salary and meaningful equity.
• Health, dental, and vision coverage.
• Flexible time off and support for experimentation, learning, and staying current with the AI ecosystem.

Compensation Range: $190K - $280K