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About the Role
This role focuses on building a product that empowers engineers to diagnose production agent failures and validate fixes. The ideal candidate will have full-stack engineering expertise with a strong understanding of LLMs and agents, capable of end-to-end product ownership from customer interaction to iteration.
Responsibilities
- Own the product that helps engineers understand why production agents are failing and whether fixes actually work.
- Talk to customers to identify problems.
- Design products.
- Build backend systems.
- Build user interfaces.
- Ship products.
- Observe product performance.
- Iterate on products.
Requirements
- 3-7 years of full-stack engineering experience.
- Strong production engineering skills.
- Experience owning systems from the data layer through the backend to the UI.
- Hands-on LLM/agent experience or compelling evidence of ability to ramp rapidly.
- Strong technical problem-solving abilities.
- Comfortable with ambiguity.
- Excellent communication skills.
- Direct customer interaction experience.
- Strong product instincts.
- High agency; ability to define what to build rather than waiting for specs.
- Ability to work in San Francisco or willingness to relocate.
- Ability to work 5 days a week in the office.
Skills
- Full-stack engineering
- LLMs
- Agents
- Production engineering
- Systems data layer
- Backend development
- UI development
- Technical problem solving
- Communication
- Customer interaction
- Product instincts
- Agent evals
- Observability
- Agent behavior monitoring
- FDE experience
- Solutions engineering
- Infrastructure
- Backend depth
- AI product experience
- Coding competitions
- Research experience
Location
- San Francisco
Work Type
- Onsite
- Full-time
Experience Level
- 3-7 years
Salary/Compensations
- $200K–$300K
Benefits
- Equity
About the Company
- The company is seeking a high-caliber full-stack/product engineer with an understanding of LLMs and agents. The focus is on full-stack engineering first, with agent depth as a secondary requirement. Candidates do not need to be hardcore agent researchers but should have hands-on LLM/agent experience or the ability to learn quickly. The role involves end-to-end ownership of customer-facing products, particularly in the 0 to 1 phase, requiring high agency and the ability to define product direction.