Agentic AI Engineer

About the role

This role focuses on developing the foundational systems that enable AI agents to operate effectively in production environments. Responsibilities include building agent runtimes and orchestration mechanisms, covering aspects like planning, tool utilization, memory management, and agent coordination. The engineer will also work on making these agents reliable through robust retry mechanisms, comprehensive failure handling, and state management, ensuring their consistent performance.

A key aspect of this position involves enhancing the observability of AI agents, which includes implementing tracing, debugging tools, and evaluation frameworks to understand and improve agent behavior. The role also emphasizes optimizing agent cost-efficiency through performance tuning and cost-aware execution strategies. Furthermore, the engineer will integrate large language models, various APIs, and external data sources into cohesive, functional systems.

The successful candidate will define the methodologies and tools developers use to construct, debug, and extend agent behaviors. This involves owning significant parts of the system and rapidly translating concepts into working products. The company prefers candidates who can collaborate effectively with a Seattle-based team, ideally within U.S. time zones, while working remotely.

The target salary range for this position is between $187,000 and $253,000.

Skills that matter here

• Python: Proficiency in Python is expected as a core language for backend and systems development in this role.
• Go: Experience with Go is valued as another core language for building robust backend and systems infrastructure.
• TypeScript: TypeScript is a relevant core language for system development, particularly where strong typing is beneficial.
• Rust: Rust is a core language option, indicating a need for performance-critical systems programming.
• LangChain: Experience with LangChain is required for building and managing agentic systems and their components.
• AutoGen: Familiarity with AutoGen is necessary for developing multi-agent or orchestration systems.

Who this role suits

• Someone who has a track record of successfully building and deploying complex systems that are relied upon by others.
• An individual with strong experience in backend and distributed systems, including APIs and infrastructure.
• A person who understands and can implement reliability patterns such as state management, retries, and observability.
• A developer who can quickly translate ideas into functional products and take ownership of significant system components.

From the employer

• 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)
• Integrate LLMs, APIs, and external data into coherent, working systems
• Define how developers build, debug, and extend agent behavior

• Evidence of building hard things that work
• Shipped real systems that people depend on
• Experience with backend/systems (distributed systems, APIs, infrastructure)
• Proficiency in at least one core language (Python, Go, TypeScript, Rust)
• Experience with reliability patterns (state, retries, observability)
• Experience with agent frameworks (LangChain, AutoGen, CrewAI)
• Experience building multi-agent or orchestration systems

• Target salary range: $187,000 - $253,000
• Other rewards may include short- and long-term incentives, and program-specific awards