Agent Systems Engineer

adaption
San Francisco, CA
Hybrid

Who this role is best for

Strong fit for engineers who build production ML or backend systems and adapt to real-world constraints, who thrive in a small, fast-paced team with a culture of direct feedback and ownership.

Best fit for

  • Engineers with 5+ years in production ML or backend systems and a track record of shipping real-world applications
    — “5+ years building production ML or backend systems, including taking LLM or agent applications from prototype to production.”
  • Candidates who value direct feedback and are comfortable with rapid iteration and unorthodox ideas
    — “We encourage bold, half-baked, and unorthodox ideas. When we disagree, we share feedback directly, never through side channels.”
  • Individuals who prioritize system reliability and can manage multi-step tasks with failure recovery in mind
    — “Improve reliability on long-running, multi-step tasks, including failure recovery.”

Things to consider

  • The role demands ownership of complex agent systems and their performance in real-world scenarios
    — “You'll own how they plan, use tools, recover from errors, and improve over time.”
  • This is a high-velocity environment that may require rapid shifts in priorities and responsibilities
    — “We operate with low egos, high velocity, and extreme ownership.”

How to stand out

  • Highlight experience in turning prototypes into real, scalable systems with measurable impact
    — “We value demonstrable output, curiosity and alignment with our core values.”
  • Showcase skills in agent design, particularly in planning, reasoning, and memory systems
    — “Strong understanding of agent design: planning, reasoning, tool use, orchestration, and memory.”
  • Emphasize your ability to build rigorous evaluation systems and ensure reproducibility
    — “Experience building rigorous evaluation systems, plus execution tracing and observability for agents, with a focus on reproducibility.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designed agent architectures
  • improved agent reliability
Typical background
AI researchML engineering

Skills & requirements

Required

Agent DesignML SystemsEvaluation SystemsReproducibilityReal-time Adaptation

Preferred

Openai Responses APIMCPServer-client Architecture

Stack & domain

AI SystemsAgent DesignPlanningReasoningTool UseOrchestrationMemoryEvaluation SystemsExecution TracingObservabilityLLM ApplicationsOpenai Responses APIMCPServer-client ArchitectureProblem-solvingTeamworkCommunicationLeadershipCuriosityAIMachine LearningBackend SystemsSoftware Engineering

About the role

Original posting from adaption via Ashby

ABOUT US

Most AI is frozen in place - it doesn’t adapt to the world. We think that’s backwards. Our mandate is to build efficient intelligence that evolves in real-time. We bring together exceptional people with the drive and creativity to push the boundaries of continual adaptation. We’re looking for builders and creative thinkers ready to shape the next era of intelligence.

Our team is small, talent-dense, and moving quickly, with a culture rooted in accountability, initiative and shared success. We look for people who care deeply, ship fast, and are eager to make a dent in the world. We operate with low egos, high velocity, and extreme ownership to build technology that expands access and benefits the many, not the few.

HOW WE WORK

  • Impact over activity: We are building a generational company. We value people who execute on ideas rather than comment from the sidelines. We believe our competitive edge lies in caring about excellence across the entire lifecycle - from research to product. No task is beneath anyone: no one is too senior to test the build, clean the data, or unblock a teammate.
  • Vulnerable, low-ego collaboration: We believe exceptional work comes from people who challenge, support and push one another to think bigger. Rapid iteration requires stepping into discomfort. We encourage bold, half-baked, and unorthodox ideas. When we disagree, we share feedback directly, never through side channels.
  • Celebrate decisively: Extraordinary effort should be deeply memorable. We celebrate milestones generously and publicly - via spot bonuses, team dinners, spontaneous gifts, and company-wide recognition - to fuel each other for the next sprint.

THE ROLE

Our vision is AI systems that are flexible, adaptable, and accessible to everyone. We believe efficiency is what makes this possible. It’s how we expand access and ensure innovation benefits the many, not the few.

You'll build the agent systems at the core of our product. These systems turn customer goals into reliable, multi-step execution across real tools and services.

This is not about building demos. You'll work on agents that operate under real constraints: incomplete information, external failures, limited budgets, and unpredictable traffic. You'll own how they plan, use tools, recover from errors, and improve over time.

WHAT YOU'LL DO

  • Design agent architectures for planning, reasoning, tool use, memory, and integration with external systems and data.
  • Improve reliability on long-running, multi-step tasks, including failure recovery.
  • Build the loops that let agents improve with real use, so performance compounds instead of staying frozen.
  • Develop evaluations that measure agent performance and resist being gamed.
  • Make practical tradeoffs between quality, latency, cost, and complexity.

SKILLS YOU'LL BRING

We look beyond traditional markers of experience. What matters most to us is what you’ve built and the impact you’ve had. We value demonstrable output, curiosity and alignment with our core values:

  • 5+ years building production ML or backend systems, including taking LLM or agent applications from prototype to production.
  • Strong understanding of agent design: planning, reasoning, tool use, orchestration, and memory.
  • Experience building rigorous evaluation systems, plus execution tracing and observability for agents, with a focus on reproducibility.
  • Familiarity with the OpenAI Responses API, MCP, and server- versus client-side execution.

Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to be perfect, but you do need to be adaptable. We encourage you to apply, even if you don't check every box.

WHAT WE OFFER

  • Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.
  • Growth paths: A dynamic environment with opportunities to take on new challenges, expand your responsibilities, and make an impact beyond your immediate role.
  • Adaption Passport: An annual travel allowance to explore somewhere new, experience different cultures and keep expanding your horizons. It can be used to travel to any country you haven’t previously been to.
  • Lunch on us: A weekly allowance for takeout or grocery delivery, wherever you are in the world. Whether it's stocking your fridge or having dinner delivered, it’s one less thing to think about.
  • Comprehensive benefits: High-quality medical coverage and benefits designed to support your health and well-being.
  • Team offsites and visits to SF HQ: We're a global team, but believe there's real value in spending time together in person. We regularly bring teammates together at our SF HQ and for team offsites in locations around the world, including London, Mexico City, and New York.

Source: adaption careers (Ashby)

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