AI Developer Platform Engineering Lead

Huxley; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Huxley is seeking an Engineering Manager to lead a hands-on team building AI-enabled development experiences. The team develops systems for software agents to operate within real engineering environments, handling agent execution, tool use, context handling, and long-running workflows.

You will grow and support the engineering team, influence technical direction, and stay closely involved in architecture and implementation across distributed systems and applied AI.

Qualifications

• Hands-on leadership of software engineering teams.
• Strong, recent hands-on experience with Go and React/TypeScript.
• Experience building applications or infrastructure around LLMs and software agents.
• Familiarity with model APIs, tool calling, context management, or iterative agent execution.
• Strong knowledge of distributed systems and cloud platforms (AWS).
• Proven ability to mentor engineers while maintaining delivery and quality.

Responsibilities

• Lead, coach, and grow a team of software engineers.
• Help set the technical direction for agent execution, integrations, and developer workflows.
• Stay close to the code and participate in architecture and implementation decisions.
• Improve how software agents use tools, manage context, stream results, and complete long-running tasks.
• Create flexible integrations that can support multiple AI models and providers.
• Partner with Product and Design to turn emerging AI capabilities into practical developer experiences.
• Improve the reliability, performance, and operational health of distributed agent systems.
• Establish clear priorities and help the team navigate technical tradeoffs.
• Maintain a strong engineering bar while creating opportunities for individual growth.

Skills

Go

React

TypeScript

Distributed systems

AWS

Mentoring

Leadership

Job description

Huxley is seeking an Engineering Manager to lead a hands-on team building AI-enabled development experiences. The team develops systems for software agents to operate within real engineering environments, handling agent execution, tool use, context handling, and long-running workflows.

You will grow and support the engineering team, influence technical direction, and stay closely involved in architecture and implementation across distributed systems and applied AI.