Staff Software Engineer, Full Stack – San Francisco

The Engineering Company; San Francisco (CA); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Competitive salary

Health, dental, and vision coverage

Flexible time off

Support for experimentation and learning

Job summary

A leading software engineering firm in San Francisco is seeking experienced staff software engineers to develop AI-driven solutions that enhance team collaboration. The ideal candidate has over 8 years in production software development, including hands-on experience with modern LLM tooling. Responsibilities include designing AI features and integrating advanced models into workflows. This position offers competitive salary, equity, and flexible time off, promoting a culture of speed, ownership, and continuous learning.

Qualifications

• 8+ years developing production software, including designing and testing at scale.
• Hands-on experience with LLM providers like OpenAI and Hugging Face.
• Familiarity with retrieval-augmented systems and safety approaches.

Responsibilities

• Design and ship AI-powered features like requirement drafting.
• Build workflows to help engineers explore designs and validate requirements.
• Integrate and optimize language models in production.

Skills

Production software development

Designing and operating cloud services

Experience with LLM providers

Prompt design

Ability to reason about tradeoffs

Comfort in fast-paced environments

Tools

TypeScript

Node.js

Python

Postgres

Job description

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.