Product Engineer (AI Agents)

Harrison Clarke; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Harrison Clarke is seeking an AI Agent Engineer to design and build production-grade AI agents for enterprise workflows. This role focuses on creating complex, reliable systems that can reason and operate in real-world environments.

The ideal candidate will have experience with LLM-powered systems, strong knowledge of agent architecture, and the ability to design scalable backend systems. Join a cutting-edge team focused on meaningful AI applications.

Qualifications

• Experience building production-ready LLM-powered systems.
• Strong understanding of agent architectures and orchestration.
• Hands-on experience with RAG, vector databases.

Responsibilities

• Designing multi-step, agentic workflows powered by LLMs.
• Shipping production-ready AI systems with reliability.
• Creating evaluation frameworks to measure agent performance.

Skills

LLM-powered systems

Agentic architectures

RAG and retrieval systems

Backend systems design

Python and APIs

LangChain or similar frameworks

Job description

Overview

AI Agent Engineer / AI Agent Builder (Startup)

We’re working with a well-funded, early-stage AI company building next-generation agentic systems for enterprise workflows.

This isn’t about simple chatbots or wrappers around APIs - this team is focused on designing production-grade AI agents that can reason, take action, and operate reliably in complex, real-world environments.

They’re looking for engineers who enjoy working at the intersection of LLMs, systems design, and product, and who want to push beyond prompt engineering into true agent architecture.

What You’ll Work On

• Designing and building multi-step, agentic workflows powered by LLMs
• Developing tool-calling systems that integrate with real enterprise software
• Building robust RAG pipelines, memory systems, and context management layers
• Creating evaluation frameworks to measure and improve agent performance
• Shipping production-ready AI systems with strong reliability, observability, and guardrails

What They’re Looking For

• Experience building LLM-powered systems in production (not just prototypes)
• Strong understanding of agentic architectures, tool use, and orchestration
• Hands-on experience with RAG, vector databases, and retrieval systems
• Ability to design scalable backend systems (Python, distributed systems, APIs)
• Familiarity with frameworks like LangChain, LangGraph, LlamaIndex, or similar
• A mindset focused on evaluation, reliability, and real-world performance

Bonus Points

• Experience with multi-agent systems or complex orchestration patterns
• Exposure to LLM evaluation, post-training, or fine-tuning workflows
• Built systems involving memory, planning, or long-running agent tasks
• Background in early-stage startups or building products from scratch

Why This Role

• Work on cutting-edge AI systems beyond typical GenAI applications
• Join a small, high-calibre team with strong technical leadership
• Own systems end-to-end, from design to production
• Meaningful impact on real enterprise use cases, not demos