Agent Engineer

London, UK / Bay Area, CA

We encourage everyone of all backgrounds and experience levels to apply


As an Agent Engineer, you'll:

  • Collaborate with the founders and team on ideas bringing technical expertise to solutions

  • Design and implement modular agent architectures with strong emphasis on reliability and verifiability

  • Develop orchestration and reasoning systems for autonomous decision-making

  • Create mechanisms for tool use, memory, and learning within agent systems including MCP

  • Build evaluation frameworks to measure agent performance and reliability

  • Integrate with modern LLM APIs and develop prompt engineering techniques, optimise and measure performance

  • Work with our customers to understand their challenges and needs


What we're looking for

  • Strong technical experience with TypeScript

  • Experience with LLM APIs (OpenAI, Anthropic, etc.)

  • Familiarity with agent architectures, limitations, and trade-offs

  • Familiarity with autonomous decision-making, reasoning, and guardrails

  • Comfort with rapid prototyping and iterative development

  • Excellent problem-solving and debugging skills


May be benefitial:

  • Background in reinforcement learning or autonomous systems

  • Understanding of evaluation methodologies for agent systems

  • Experience with multi-agent systems


If you're passionate about pushing the boundaries of what autonomous AI agents can do and want to help shape this emerging technology, we'd love to hear from you.


As our Agent Engineer, you'll spearhead the development of our core agent architecture and capabilities. You'll work with a multidisciplinary team to design and implement autonomous systems that can reason, plan, and act effectively.


As an Agent Engineer, you'll:

  • Collaborate with the founders and team on ideas bringing technical expertise to solutions

  • Design and implement modular agent architectures with strong emphasis on reliability and verifiability

  • Develop orchestration and reasoning systems for autonomous decision-making

  • Create mechanisms for tool use, memory, and learning within agent systems including MCP

  • Build evaluation frameworks to measure agent performance and reliability

  • Integrate with modern LLM APIs and develop prompt engineering techniques, optimise and measure performance

  • Work with our customers to understand their challenges and needs


What we're looking for

  • Strong technical experience with TypeScript

  • Experience with LLM APIs (OpenAI, Anthropic, etc.)

  • Familiarity with agent architectures, limitations, and trade-offs

  • Familiarity with autonomous decision-making, reasoning, and guardrails

  • Comfort with rapid prototyping and iterative development

  • Excellent problem-solving and debugging skills


May be benefitial:

  • Background in reinforcement learning or autonomous systems

  • Understanding of evaluation methodologies for agent systems

  • Experience with multi-agent systems


If you're passionate about pushing the boundaries of what autonomous AI agents can do and want to help shape this emerging technology, we'd love to hear from you.


Interested in this role or know someone who may be?
Send a message to founders@stuntdouble.io

Stunt Double, Aictor, and Turnout Labs are registered trademarks of Turnout Labs Ltd

Stunt Double, Aictor, and Turnout Labs are registered trademarks of Turnout Labs Ltd