Staff Software Engineer
Flow Engineering
Listing collected from Flow Engineering's career site. NextChapter is independent of Flow Engineering.
San Francisco, CA · $260k–$300k a year · Posted March 11, 2026
Just laid off? Start here: a plan for the first weeks
See every open role at Flow Engineering
More in California job market · Staff Software Engineer jobs in San Francisco, CA (216) · All Staff Software Engineer jobs (941) · Manufacturing & Industrial · Engineering jobs
More roles at Flow Engineering
- Head of Forward Deployed Engineering · San Francisco, CA
- Head of Revenue Operations & GTM Engineering · San Francisco, CA
- Account Executive - Enterprise · San Francisco, CA
- Account Executive, Mid-Market · San Francisco, CA
- Field Account Executive, Mid-Market · San Francisco, CA
- Revenue Operations/GTM Engineer · San Francisco, CA
Similar jobs
- Software Engineer, ML Developer Experience · AnyScale · San Francisco, CA
- Member of Technical Staff - Post-Training · Reflection AI · San Francisco, CA
- Software Engineer, Embedded Linux · Chariot Defense · San Bruno, CA
- Software Engineer, Growth Data Platform · Omni · San Francisco, CA
- Staff Engineer, Full Stack (US, Canada, SF) · Short Story · San Francisco, CA
- Member of Technical Staff - Engineering Lead, Compute Platform · Reflection AI · San Francisco, CA
Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing pays about $280,000 a year. Across 229 open staff software engineer listings that state pay, the middle half runs $218,000 to $260,000 and the median is $242,000. That is 16% above the median, above the middle half of those listings.
Listed pay is what employers advertise, not what people are paid.
Staff Software Engineer salaries by state · Check your own pay
How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
Say which you have and which you want to build. We use it to match you to jobs like this one.
About the job
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 staff 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
- 8+ 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.