Senior/Staff FDE - CUA

About Snorkel

Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. 

Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

About the Role

Snorkel AI is hiring a Forward Deployed Engineer focused on Computer Use Agents to partner with leading AI labs and enterprises on their most critical agentic-AI initiatives.

In this role, you will lead the technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks. You will translate ambiguous product and model challenges into robust task environments, datasets, evaluators, and delivery plans that improve agent reliability and downstream performance.

You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements.

Main Responsibilities

Computer Use Agents, Data, and Evaluation

Design and build task environments, datasets, and evaluation workflows for computer-using agents operating across browsers, desktop applications, terminals, and other software interfaces

Translate customer goals, agent failure modes, and real-world workflows into representative, multi-step tasks with clear success criteria

Develop data-generation, validation, and quality-assurance pipelines for multimodal and agentic training and evaluation data

Build automated evaluators, checks, and measurement frameworks to assess task completion, correctness, robustness, efficiency, and adherence to requirements

Diagnose agent failures across planning, tool use, perception, state management, and interaction with user interfaces; turn findings into improved tasks, data, and evaluations

Design and run experiments to measure how data, task design, and evaluation changes affect downstream agent performance

Deliver reusable, production-grade task suites, datasets, and evaluation assets that help customers train, benchmark, and improve computer-use agents

Forward Deployed Engineering & Customer Partnership

Lead technical workstreams from initial solution design through production delivery, navigating ambiguity and making sound technical decisions

Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value

Rapidly prototype and productionize solutions across models, agent frameworks, APIs, browser or desktop environments, and custom applications

Communicate technical tradeoffs, experimental results, and recommendations clearly to technical and cross-functional stakeholders

Serve as a trusted technical partner to customers and internal delivery teams, resolving complex blockers and driving alignment

Technical Leadership & Scale

Identify recurring patterns across customer engagements and turn successful solutions into reusable task frameworks, evaluators, tooling, and best practices

Define and improve technical standards for agent task design, environment reliability, evaluation, and delivery

Partner with DaaS Engineering, Research, and Product teams to influence platform and product capabilities based on real-world customer needs

Lead technical design reviews, share expertise, and provide guidance to other engineers

Stay current with emerging agentic-AI, computer-use, evaluation, and data-curation techniques and assess their applicability to customer problems

Wha …