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Senior/Staff Forward Deployed Engineer – Computer Use Agents
Snorkel AI. Lead technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning engineering and software development, with a strong focus on building and evaluating agentic systems and task environments. Proficient in Python and experienced in delivering production-grade solutions while collaborating with cross-functional teams.
Highest-signal resume keywords
Machine Learning EngineeringPython ProgrammingTask Environment DesignAgent Evaluation TechniquesTechnical Communication
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningSoftware EngineeringData Pipeline DevelopmentAPI DevelopmentTask Suite CreationDataset ValidationReinforcement LearningExperimental DesignData AnalysisAgent Benchmarking
Soft Skills
Technical CommunicationProblem-SolvingCollaborationCustomer EngagementInfluencing Decisions
Tools & Technologies
GenAILLM StackAutomation ToolsWeb ApplicationsDesktop ApplicationsDeveloper ToolsEvaluation FrameworksData Validation ToolsAgent FrameworksBrowser-Based Systems
Industry Keywords
Agentic SystemsComputer-Using AgentsEvaluation TechniquesMultimodal ModelsTechnical StandardsProduction DeliveryCross-Functional CollaborationCustomer-Facing EnvironmentsData CurationEmerging AI Techniques
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Lead technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks
- Translate ambiguous product and model challenges into robust task environments, datasets, evaluators, and delivery plans that improve agent reliability and downstream performance
- Work across the full delivery lifecycle from technical discovery and solution design through implementation, evaluation, and production delivery
- Identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements
- Design and build task environments, datasets, and evaluation workflows for computer-using agents
- 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
- Diagnose agent failures across planning, tool use, perception, state management, and user-interface interaction
- Design and run experiments measuring effects of data, task design, and evaluation changes on agent performance
- Deliver reusable, production-grade task suites, datasets, and evaluation assets
- Lead technical workstreams from solution design through production delivery
- Prototype and productionize solutions across models, agent frameworks, APIs, browser or desktop environments, and custom applications
- Communicate technical tradeoffs, experimental results, and recommendations to technical and cross-functional stakeholders
- Serve as a trusted technical partner to customers and internal delivery teams
- 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
- Lead technical design reviews, share expertise, and guide other engineers
- Stay current with emerging agentic-AI, computer-use, evaluation, and data-curation techniques
Requirements
What you’ll need- 5+ years of experience in machine learning engineering, software engineering, applied AI, forward deployed engineering, solutions engineering, or a similar technical role
- Strong Python skills and experience building reliable production software, data, or ML systems
- Hands-on experience building, evaluating, or deploying LLM-based or agentic systems, including computer-use agents (CUA)
- Strong understanding of experimentation and evaluation, including LLM-as-a-judge / model-based evaluation, defining metrics, and using empirical results to guide technical decisions
- Experience designing task environments, datasets, and verifiers for agents, including reward & verifier design (RL with verifiable rewards)
- Experience building or working with APIs, automation, web applications, browser-based systems, desktop applications, or developer tools
- Experience manipulating, analyzing, and validating large or complex datasets using Python and the modern GenAI/LLM stack
- Demonstrated ability to take ambiguous technical problems from problem definition through implementation and delivery
- Strong technical communication skills and experience working directly with customers or cross-functional stakeholders
- Demonstrated experience setting technical direction, creating reusable approaches across projects, and influencing broader engineering or product decisions
- Experience developing agent benchmarks, task suites, or simulators
- Experience with multimodal models, visual grounding, or evaluating agents that interact with graphical user interfaces
- Experience with repo-scale agentic coding tasks, agent tool protocols & interop, or productized browser/computer-use agents
- Experience building data pipelines for fine-tuning, reinforcement learning, preference optimization, benchmarking, or model evaluation
- Experience working in fast-paced, customer-facing environments where requirements and technical approaches evolve quickly
Benefits
Comp & perks- Variable compensation opportunity
- Equity
- Benefits
- Meaningful opportunities to shape priorities and initiatives
- Opportunities to influence key strategic decisions
- Support for building a career through technical deepening, leadership opportunities, and learning new skills
- Reasonable accommodation for individuals with disabilities