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Member of Technical Staff, Agent Harness

Mirendil

United States, CAFull-time$300–400K/yrPosted 2mo agoVerified open 3 days ago

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At a glance

Compensation
$300–400K/yr
Location
United States, CA
Schedule
Full-time
Work Authorization
Not specified

Job overview

Mirendil seeks an engineer passionate about building tools that enable frontier AI models to perform optimally, focusing on efficient architectures, agent harnesses, orchestration systems, guardrails, and observability tooling to scale agentic tasks.

Skills & qualifications

RequiredNice to have

Skills

Model ArchitectureTool IntegrationScalable SystemsReliability EngineeringObservability

Full job description

Mirendil Mirendil is a tech-first company focused on solving core bottlenecks that unlock step-change acceleration across science and technology. Our first goal is to democratize frontier AI R&D across scientific disciplines. We are building a frontier AI research company and training our own models end-to-end.

The Role We are looking for an engineer who is passionate about giving the model tools to perform the best it can. We want people who deeply understand model capabilities and can build efficient architectures for the model and researchers to work across. If you have a penchant for building your own tools, this role will be a good fit. Some example areas you might work on:

  • Build and innovate on the agent harness: agent loop architecture, tool integrations, prompt scaffolding, execution environments, and capability primitives

  • Design orchestration systems for horizontal scaling of agents: memory, state management, multi-agent coordination, and task decomposition

  • Build guardrails and reliability mechanisms that make long-horizon agentic tasks robust across failures, unexpected model behavior, and edge cases

  • Own the extension layer between our models and external tools, APIs, and environments - making it fast to bring new capabilities online

  • Develop evaluation and observability tooling so the team can measure agent behavior, catch regressions, and iterate quickly

If you're excited about building the infrastructure that makes agents actually work at scale, we'd love to hear from you.

We offer a base salary of $300,000–$400,000 USD and a meaningful equity grant, depending on experience and background, along with competitive benefits.

You've read the whole posting — now see how you match it.