Product Engineer, Talent Experience

Location: San Francisco, CACompany Stage of Funding: Series C AI Company ($10B Valuation)Office Type: Onsite (5 Days Per Week)Salary: $130,000–$400,000 + Equity

Company Description

We're representing one of the fastest-growing AI companies building the infrastructure that connects human expertise with frontier models. Its platform supports a global network of domain experts who help train and evaluate advanced AI systems, while its enterprise products help large organizations capture expert workflows and translate that knowledge into AI agents.

The company is profitable, valued at approximately $10 billion, and operates at significant scale across AI data, evaluation, and enterprise workflows. This role sits on the Talent Experience team, which builds the systems used to assess, verify, and continuously evaluate expert talent.

What You Will Do

• Design, build, and ship backend services and APIs that power a large-scale assessment platform.
• Own features end-to-end, from product discussions and technical design through implementation, testing, and release.
• Build evaluation pipelines and data models that combine human judgment with AI-powered scoring.
• Develop candidate- and expert-facing product experiences across the full stack.
• Partner closely with Product, AI, and Data teams to translate assessment research into production systems.
• Improve the performance, reliability, and observability of core assessment infrastructure.
• Build systems supporting AI-assisted interviews, skill verification, and expert evaluation.
• Use modern AI-assisted development tools to increase engineering velocity while maintaining a strong quality bar.
• Continuously improve candidate and expert experiences based on real product usage and customer needs.
• Take significant ownership over roadmap execution within a small, high-velocity team.

Ideal Background

• 3+ years of professional software engineering experience building production systems.
• Strong backend engineering fundamentals across API design, data modeling, distributed systems, and relational databases.
• Comfortable working across the full stack when needed.
• Experience with modern frontend frameworks such as React and TypeScript.
• Strong software engineering fundamentals, including testing, debugging, and performance optimization.
• Proven ability to own meaningful product features from design through production.
• Strong product intuition with a genuine interest in building user-facing software.
• Comfortable operating in fast-moving environments with evolving priorities.
• High ownership, curiosity, and a bias toward shipping.
• Experience using modern AI coding tools such as Cursor, Claude Code, GitHub Copilot, Codex, or similar.

Preferred

• Experience building or integrating LLM-powered features in production.
• Background building assessment, evaluation, workflow, marketplace, or productivity products.
• Experience designing data models or pipelines that combine AI outputs with human review.
• Familiarity with distributed systems and high-throughput backend infrastructure.
• Startup experience with significant end-to-end product ownership.
• Experience collaborating closely with product managers, researchers, and data teams.
• Strong understanding of frontend/backend tradeoffs in product-oriented engineering environments.
• Interest in AI infrastructure, evaluation systems, and human-in-the-loop products.

Compensation and Benefits

• Base salary: $130,000–$400,000.
• Generous equity grant vested over four years.
• Bi-annual performance bonus structure.
• Up to $15,000 relocation bonus.
• $10,000 proximity bonus for employees living within 0.5 miles of the office.
• $1,500 monthly meal stipend.
• Complimentary Equinox membership.
• $200 monthly laundry reimbursement.
• $200 monthly personal wellness reimbursement.
• Comprehensive medical, dental, and vision insurance.
• Five days per week onsite in San Francisco.
• High-impact opportunity to build the systems that determine how tens of thousands of experts are evaluated and matched to frontier AI work.