Senior Agentic AI Engineer
Role in brief
Eigen Labs is seeking a Senior Agentic AI Engineer to develop core systems for AI agents. This role involves building reliable, observable, and cost-effective agent runtimes and orchestration systems. Ideal candidates have experience shipping production systems, deep understanding of agent systems or LLM pipelines, and strong backend/systems skills, particularly with distributed systems and APIs.
About the role
This Senior Agentic AI Engineer role focuses on creating robust and efficient AI agent systems. You will be responsible for building agent runtimes and orchestration, ensuring agents are reliable through effective failure handling and state management. A key aspect of the work involves making these systems observable for debugging and evaluation, and optimizing them for cost-effective execution in production environments.
The position requires integrating large language models (LLMs), APIs, and external data sources into cohesive, functional systems. You will also define how other developers build, debug, and extend agent behavior, emphasizing practical, production-ready solutions over demonstrations. The company values individuals who can translate ambiguous problems into working products that users depend on.
Eigen Labs is building open networks to counter the concentration of power in AI, advocating for open science and individual agency. The team is looking for engineers who are passionate about coordination systems and agentic infrastructure. Success in this role means delivering agent systems that are not only functional but also reliable, observable, and cost-efficient, contributing to the broader mission of open AI development.
The annual salary for this position ranges from $187,000 to $253,000 USD.
Skills that matter here
- Go: Proficiency in Go is valued as part of the core language requirements for backend and systems development.
- Python: Python proficiency is a strong technical foundation for developing agent systems and LLM pipelines.
- Rust: Experience with Rust is beneficial for building performant and reliable backend and systems infrastructure.
- TypeScript: TypeScript is listed as a core language, indicating its use in developing parts of the agent systems or related tools.
Who this role suits
- A builder who has successfully delivered complex, production-grade systems that others rely on.
- Someone who can navigate ambiguity, transforming ill-defined problems into concrete, working solutions.
- An engineer with a deep understanding of how systems behave in production, including failure modes and reliability trade-offs.
- A fast-paced individual who prioritizes iteration and action over waiting for perfect specifications.
From the employer
What You Will Do
- Build agent runtimes and orchestration systems (planning, tool use, memory, coordination)
- Make agents reliable (retries, failure handling, state management)
- Make agents observable (tracing, debugging, evaluation)
- Make agents cheap (cost-aware execution, performance optimization)
- Make agents useful in production (not demos - real systems people depend on)
- Integrate LLMs, APIs, and external data into coherent, working systems
- Define how developers build, debug, and extend agent behavior
What You’ll Bring
We care more about evidence than years of experience. Show us you’ve built hard things that work.
Strong signals we look for
- You’ve shipped real systems that people depend on
- You’ve taken ambiguous problems and turned them into working products
- You’ve built or deeply explored agent systems, LLM pipelines, or automation beyond simple demos
- You understand system behavior in production - failure modes, tradeoffs, reliability
- You move fast and iterate - you don’t wait for perfect specs
Technical foundation we look for
- Strong backend / systems experience (distributed systems, APIs, infrastructure)
- Proficiency in at least one core language (Python, Go, TypeScript, Rust, etc.)
- Experience with reliability patterns (state, retries, observability)
- Comfort working across the stack when needed
Nice To Have
- Experience with agent frameworks (LangChain, AutoGen, CrewAI, or custom systems)
- Experience building multi-agent or orchestration systems
- Familiarity with LLM evaluation, prompting, or performance tuning
- Experience with workflow engines (Temporal, Airflow, Dagster)
- Experience building developer platforms, SDKs, or internal tools
- Exposure to retrieval systems, vector databases, or memory architectures
- Interest in crypto, distributed systems, or verifiable compute
US Benefits
- Competitive salary and non-cash compensation (tokens and equity)
- World class benefits package (medical/dental/vision)
- Remote work set up stipend
- Flexible hours and a supportive remote environment
- Flexible time off
- 401(k) retirement plan + company match
- Monthly wellness benefit
- Yearly off-sites
- Paid parental leave
If hired outside of the US through an EOR, benefits will be offered based on specific country requirements and EOR offerings.
Questions about this role
What is the remote work policy for this role?
This is a fully remote position, with benefits offered based on specific country requirements if hired outside the US through an Employer of Record.
What level of seniority is expected for this position?
This is a senior-level role, and candidates are expected to have a strong background in shipping real systems and tackling ambiguous problems.
What technical skills are important for this role?
Key technical skills include strong backend/systems experience, proficiency in at least one core language like Python, Go, TypeScript, or Rust, and familiarity with reliability patterns such as state management, retries, and observability.
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