Production AI Agent Engineer: Build Scalable Workflows

Harrison Clarke; San Francisco (CA); On-site; USD 150,000 - 250,000; Full time

Job summary

Harrison Clarke in San Francisco is seeking an experienced software engineer to design, build, and ship AI agents and agentic workflows into production.

You will develop systems that enable AI agents to reason, use tools, retrieve information, and complete complex tasks, with a focus on reliability and production readiness.

This is a fast-moving, high-growth environment where experimentation and iteration are encouraged, and where your work directly contributes to scalable healthcare AI solutions.

Qualifications

• Strong software engineering fundamentals and experience building production systems.
• Demonstrated experience building and shipping AI agents into production.
• Practical understanding of agentic architectures, workflows, tool use, and RAG.
• Experience debugging, evaluating, and improving AI agent behaviour.

Responsibilities

• Design, build, and ship AI agents and agentic workflows into production.
• Develop systems that enable AI agents to reason, use tools, retrieve information, and complete complex tasks.
• Build and improve RAG systems, agent harnesses, and supporting infrastructure.
• Debug and evaluate agent behaviour across real-world use cases.
• Identify failure modes and develop strategies to improve agent reliability, accuracy, and consistency.
• Work closely with product and engineering teams to turn emerging AI capabilities into production-ready experiences.
• Develop evaluation and quality frameworks to understand how agents perform and where they need improvement.

Skills

AI agents

Production systems

Agentic architectures

Debug AI behaviour

Tools

Agent frameworks

RAG tooling

Job description

Harrison Clarke in San Francisco is seeking an experienced software engineer to design, build, and ship AI agents and agentic workflows into production.

You will develop systems that enable AI agents to reason, use tools, retrieve information, and complete complex tasks, with a focus on reliability and production readiness.

This is a fast-moving, high-growth environment where experimentation and iteration are encouraged, and where your work directly contributes to scalable healthcare AI solutions.