Product Engineer, Talent Experience

About the role

You will design, build, and ship backend services and APIs that power Mercor's assessment platform at scale, owning the systems that evaluate the skills and expertise of the world's top talent. You will own features end-to-end - from product discussions and technical design to implementation, testing, and release - working directly with the Assessment product lead on roadmap and execution from day one. You will build evaluation pipelines and data models that combine human judgment with AI-powered scoring, contributing across both the candidate- and expert-facing product surfaces of assessment flows. This is a high-leverage role where improvements to assessment quality and throughput compound across everything Mercor does, and you will partner closely with Product, AI, and Data teams to translate assessment research into production systems. You will leverage modern AI coding tools to accelerate development while maintaining a high engineering bar, and you will continuously improve the performance, reliability, and observability of assessment infrastructure to solve real customer problems. Your work will directly enhance candidate and expert experience as you solve real-world problems and refine the systems that match experts to the most important AI work.

Key facts

What you'll do

• Design, build, and ship backend services and APIs that power Mercor's assessment platform at scale.
• Own features end-to-end - from product discussions and technical design to implementation, testing, and release.
• Build evaluation pipelines and data models that combine human judgment with AI-powered scoring.
• Contribute across the stack, including the candidate- and expert-facing product surfaces of assessment flows.
• Partner closely with Product, AI, and Data teams to translate assessment research into production systems.
• Leverage modern AI coding tools to accelerate development while maintaining a high engineering bar.
• Improve the performance, reliability, and observability of assessment infrastructure.
• Solve real customer problems and continuously improve candidate and expert experience.
• Implement robust testing strategies to ensure correctness and reliability of assessment components.
• Collaborate with cross-functional stakeholders to gather requirements and align on assessment objectives.
• Instrument services for monitoring and debugging to support rapid iteration and reliability.
• Refine data models used for skill verification and scoring to adapt to evolving expert domains.
• Optimize API latency and throughput to support tens of thousands of concurrent evaluations.
• Maintain and evolve the candidate and expert interfaces to ensure clarity and usability in assessment flows.
• Track and report on key assessment metrics to inform product decisions and improvements.

Requirements

• 3+ years of professional software engineering experience building production systems.
• Strong backend fundamentals: API design, data modeling, distributed systems, and relational databases.
• Comfortable working across the stack, including modern frontend frameworks (e.g. React/TypeScript) when the product needs it.
• Experience building or integrating LLM-powered features in production is a strong plus.
• Comfortable building products using modern AI development tools (e.g. Cursor, Claude Code, GitHub Copilot, Codex, or similar) to accelerate software development.
• Strong software engineering fundamentals, including testing, debugging, and performance optimization.
• Excellent product intuition - you enjoy building products that people actually use.
• Comfortable working in fast-moving environments with evolving priorities.
• High ownership, curiosity, and a bias toward shipping.
• Ability to communicate clearly and collaborate effectively with cross-functional teams.
• Willingness to work in-person in San Francisco five days a week as part of the Mercor community.
• Commitment to learning and applying new tools and techniques in a fast-evolving AI landscape.
• Understanding of evaluation methodologies and the importance of reliable skill verification at scale.

Nice to have

• Experience with large-scale data pipelines and real-time processing.
• Familiarity with AI benchmarking and evaluation frameworks.
• Contributions to open-source projects related to assessment, testing, or data validation.
• Background in human-in-the-loop systems or human expertise platforms.
• Knowledge of compliance and privacy considerations for handling expert data.
• Experience working with high-velocity product roadmaps in AI-focused companies.

Practical notes

You will work in-person five days a week in our San Francisco, NYC, or London offices.