Full Stack Engineer

Location: San Francisco, CA
Compensation: $230K–$300K base + competitive equity
Visa: Open to visa transfers (OPT, H-1B); additional sponsorship reviewed case-by-case for exceptional candidates
Experience: 5–8 years (confirm: initial role description also says 2–5 years)
Office Type: On-site, 5 days per week
Employment Type: Full-time
Hiring Count: Not specified

Company Description

We are building infrastructure that helps teams developing autonomous AI agents understand, monitor, and improve how their systems behave in production.

As AI agents become more capable and are deployed across increasingly complex workflows, understanding their behavior and identifying why they fail becomes critical. Our platform helps engineering teams investigate agent interactions, identify behavioral patterns, debug failures, and improve reliability through structured evaluations and verification workflows.

The engineering team is small, fast-moving, and focused on building tools that solve challenging problems for developers working with production AI systems. Engineers have significant ownership over product development, from understanding customer problems and defining solutions to building and iterating on the product.

We are looking for a backend-leaning Full Stack Engineer who enjoys building great software, working through ambiguity, and taking ownership of problems end-to-end. The role offers the opportunity to work across APIs, data models, internal systems, and polished product experiences while building tools that AI engineering teams rely on.

What You Will Do

1. Build Core Product Experiences

• Build core product experiences across investigation interfaces, evaluation workflows, debugging tools, verification, and replay systems.

• Develop interfaces that help engineers understand complex agent behavior, investigate failures, and identify patterns across production interactions.

• Build intuitive product surfaces that make complex technical workflows easier to understand and use.

• Contribute to the development of tools that help AI teams improve the reliability of their production agents.

2. Own Problems End-to-End

• Talk directly with customers to understand where their agents fail and what problems they need to solve.

• Define product requirements, identify solutions, build features, and iterate based on customer feedback.

• Take ownership of projects from problem discovery through implementation and delivery.

• Work through ambiguous problems independently and turn them into practical product solutions.

3. Build Across the Full Stack

• Ship across the full stack, with a stronger emphasis on backend engineering.

• Design and implement APIs, data models, internal systems, and product interfaces.

• Build platform infrastructure including workspaces, permissions, billing, usage systems, and SDKs.

• Contribute to terminal-first developer experiences and integrations.

• Build scalable, maintainable systems that support complex agent investigation workflows.

4. Build AI-Powered Investigation Systems

• Contribute to the development of an agent that runs large-scale investigations across production traces.

• Build systems that help investigate agent failures, tool errors, behavioral regressions, instruction drift, and edge cases.

• Work with production agent traces and turn complex interaction data into actionable insights.

• Collaborate with AI teams to understand agent behavior and translate their challenges into product improvements.

5. Work Directly with AI Engineering Teams

• Work closely with teams building and deploying production AI agents.

• Understand how their agents behave, where they fail, and what makes them unreliable.

• Translate real-world customer problems into product and engineering decisions.

• Help build tools that allow developers to debug, evaluate, and improve their agents.

Ideal Candidate Background

• 5–8 years of experience in full-stack product engineering, with a backend-leaning profile. Confirm experience range with the hiring team, as the initial role description also states 2–5 years.

• Has shipped production products end-to-end.

• Strong backend engineering fundamentals and experience building APIs, data models, and internal systems.

• Comfortable working across the full stack, including frontend product interfaces.

• Experience building high-quality software at reputable technology companies or Series B+ startups.

• Comfortable operating in a fast-paced, ambiguous startup environment.

• Strong ownership mindset and ability to take projects from customer discovery through implementation and iteration.

• Enjoys building developer-facing products and solving complex engineering problems.

Bonus Points

• Experience with AI agents or agentic systems.

• Experience building developer tools.

• Experience with observability, monitoring, or debugging products.

• Experience working with production AI systems and agent traces.

• Familiarity with evaluation, verification, and replay workflows.

Technical Requirements

Core Stack

• TypeScript

• React

• Next.js

• Python

• Node.js

• PostgreSQL

Engineering Requirements

• Strong full-stack product engineering experience.

• Backend-leaning engineering capabilities.

• Experience building APIs and data models.

• Experience developing complex product interfaces.

• Ability to work across frontend, backend, and platform systems.

• Experience shipping production software end-to-end.

• Strong engineering fundamentals and ability to work independently.

Compensation & Benefits

• Base Salary: $230K–$300K.

• Equity: Competitive equity.

• Visa: Open to visa transfers, including OPT and H-1B transfers. Additional sponsorship reviewed case-by-case for exceptional candidates.

• Work Model: Full-time, on-site in San Francisco, five days per week.