San Francisco, CA · Hybrid · Full-time
Compensation: $220K–$315K + equity
About the Company
Our client is a Series C, AI-native platform that is changing how audit, advisory, and assurance work gets done. Built for regulated environments, the platform pairs practitioners with agentic AI to modernize engagement delivery from planning through close. Big Four and mid-tier firms run on it, including more than half of the top 100 accounting and consulting firms, and the company recently closed a Series C from leading growth and venture investors.
Founded 2019 · ~150 people · Industry: AI, Finance, B2B Software
The Role
You'd join the team that owns the long-horizon agents at the core of the client's AI platform, with a primary focus on their Financial Audit product, the company's largest product line and its next growth engine. The work sits at the frontier of AI product development: agent knowledge, evaluation, and driving quality and reliability at scale. You'd take real ownership of how the team measures and improves agent quality, building on AI infrastructure that is already in place. The agents you ship are used by Big Four firms in production.
What you'll be doing
- Set the evals strategy and error-analysis practice that defines how the team measures and improves agent quality
- Design and build agent knowledge and evaluation infrastructure for long-horizon agents
- Lead error analysis on agent behavior and turn findings into platform-level reliability fixes
- Build and harden the backend systems that support agent execution, evaluation, and monitoring at scale
- Help drive the platform's reliability and quality roadmap alongside the broader AI team
- Mentor engineers and raise the bar on eval rigor across the team
Tech stack: Language-agnostic; the team builds with coding agents as part of its day-to-day workflow
Requirements
- Currently operating at a Senior, Staff, or Tech Lead level (or higher); strong founders are also considered
- Roughly 6–15 years of professional software engineering experience
- One to two years spent building end-to-end agents or production AI platforms, including agentic loops, evals, and error analysis
- Hands-on backend work on customer-facing agents that run in production at scale
- Solid background in backend platform, data platform, or full-stack engineering
- Computer science degree from a top-tier program (US or international)
- Able to work hybrid from the San Francisco office, averaging about three days a week on-site
Nice to Haves
- Time at a recently IPO'd tech company or an AI-native startup
- Distributed systems experience
Why Join
- Build customer-facing agents for the client's biggest product, used by Big Four firms at scale
- Own agents, evals, and workflows on top of AI infrastructure that's already built
- Well-capitalized, late-stage company with a recently closed Series C and marquee investors
- Work on open problems in agent reliability that don't have established playbooks yet
- Twice-yearly in-person offsites; the team averages ~3 days a week in office with no set days
Details
- Location: San Francisco, CA
- Work policy: Hybrid, averaging ~3 days/week in office (team average, no set days)
- Compensation: $220K–$315K + equity (range spans Senior through Staff)
- Visa sponsorship: Open to visa transfers (e.g. OPT, H-1B transfers)
- Employment type: Full-time