Job Description
Staff AI Software Engineer
Compensation: Up to ~$300k base + Equity
Location: San Francisco, Hybrid 2 day in office
About the Company
A fast-scaling, venture-backed SaaS company is modernizing a large, specialist professional services market through workflow automation and applied AI.
The company is building mission-critical software for complex assurance and advisory workflows, helping expert teams move faster, improve quality, and automate highly manual knowledge work. Following significant recent funding, AI is now a central pillar of the product and engineering roadmap with executive-level backing and a major push to rebuild core platform capabilities around applied AI, evaluations, ingestion, observability, and production-grade AI infrastructure.
The Role
We’re looking for a Staff AI Software Engineer to help shape and scale the AI platform behind a new generation of intelligent workflow products.
This is a high-ownership IC role for someone who has shipped real AI systems into production and wants to work at the intersection of LLMs, infrastructure, product engineering, and domain-specific automation. You’ll work closely with senior engineering, product, design, and domain experts to turn complex professional workflows into reliable AI copilots and automation systems used by customers in production.
What You’ll Do
- Build and scale AI platform capabilities across evaluations, ingestion pipelines, observability, and AI/ML infrastructure.
- Own end-to-end development of applied AI systems, from prototype through production deployment.
- Design and improve RAG pipelines, embeddings workflows, prompt systems, and model interaction patterns.
- Develop tooling for system evaluation, monitoring, versioning, orchestration, and quality control across LLM-powered products.
- Partner with product, design, engineering, and domain specialists to translate complex workflows into usable AI-powered product experiences.
- Help define engineering standards for production AI systems, with a focus on reliability, maintainability, and measurable quality.
- Contribute to the broader AI technical direction across the company as the platform scales.
What You’ll Bring
- Strong software engineering experience across backend, systems, distributed systems, infrastructure, or platform engineering.
- Proven experience shipping AI systems into production, ideally involving LLMs, RAG, NLP, AI agents, evals, observability, ingestion, or AI/ML infrastructure.
- Strong Python skills and the engineering depth to succeed in rigorous coding and systems design interviews.
- A pragmatic builder mindset: you care about shipping, quality, reliability, and avoiding brittle “demo-only” AI systems.
- Comfort working in high-calibre technical teams where ownership, pace, and judgment matter.
- Ability to collaborate closely with cross-functional partners and domain experts on complex, ambiguous product problems.
- Strong attention to code quality, system design, and the limitations of AI-generated output.
About People In AI
People In AI partners with some of the world’s most ambitious AI, ML, and data-driven companies to help them build exceptional technical teams. We work closely with high-growth startups, scaleups, and research-led organizations across applied AI, foundation models, infrastructure, data, and product engineering.