Distyl AI · San Francisco
Data & AIEngineeringRemoteFullTimeposted 2mo ago
Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.
We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.
Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s.
At Distyl, we build AI systems using Evaluation-Driven Development—an approach where evaluation is not an afterthought, but the primary mechanism for iterating, improving, and trusting AI behavior in production.
AI Evaluation Engineers focus on designing and implementing the evaluation systems that drive this process. They are hands-on engineers who write production Python code, build evaluation pipelines, and use structured signals to guide system design, prompt iteration, and deployment decisions for real customer-facing AI systems.
This role is for engineers who believe that AI systems only improve when measurement is tightly coupled to development—and who want to apply that philosophy directly to systems that matter.
Design and implement evaluation frameworks that enable Evaluation-Driven Development for AI systems deployed in customer environments
Define how system quality is measured in each domain, ensuring that evaluation signals reflect real user needs, domain constraints, and business objectives
Build and maintain golden test cases and regression suites in Python, using both human-authored and AI-assisted test generation to capture critical behaviors and edge cases. These test suites are treated as first-class system components that evolve alongside the AI system itself
Develop and maintain evaluation pipelines—offline and online—that integrate directly into system iteration loops. Evaluation results inform prompt design, agent logic, model selection, and release readiness, ensuring that system changes are driven by measurable improvements rather than intuition alone
Define, calibrate, and operate LLM-based graders, aligning automated judgments with expert human assessments. They investigate where evaluation signals diverge from real-world outcomes and refine grading approaches to maintain signal quality as systems and domains evolve
Work closely with Forward Deployed AI Engineers, Architects, Product Engineers, AI Strategists, and domain experts to ensure evaluation frameworks meaningfully guide system development and deployment in production
5+ years of software engineering experience
Strong Python Engineering Skills: Write clean, maintainable Python and are comfortable building evaluation and experimentation pipelines that run in production environments. You treat evaluation code with the same rigor as application code
Experience with Evaluation-Driven or Experiment-Driven Development: Experience using structured evaluation or experimentation frameworks to drive system iteration, and understand the pitfalls of overfitting to metrics that don’t reflect real outcomes
Ability to Translate Human Judgment into Code: Work with subject matter experts to elicit high-quality judgments and encode them into test cases, scoring functions, and graders that scale
Systems-Oriented Mindset: Understand how evaluation interacts with prompts, agents, data, and deployment. You design evaluation systems that support fast iteration while maintaining trust and safety in production
AI-Native Working Style: Use AI tools to generate tests, analyze failures, explore edge cases, and accelerate debugging and iteration
Travel: Travel between 10-50% of the time, depending on the project, your role and level of interest in doing so
The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible time off
Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources
Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot
Complimentary in-office lunches and snacks provided
Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems
Ownership of high-impact projects across top enterprises
A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence
Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office..
#LI-Hybrid
We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.