Agent Builder

Harrison Clarke; San Jose (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Harrison Clarke is partnering with a well-funded early-stage AI startup building enterprise AI infrastructure that enables autonomous agents to execute complex workflows across mission-critical software systems. You'll work on infrastructure that allows AI to reliably interact with real business systems at scale.

As one of the earliest AI engineers, you'll own core agent architecture from development through production deployment, building multi-agent systems, tool-calling pipelines, and AI

Job description

Other office locations - NYC and Seattle

We're partnered with a well-funded early-stage AI startup building enterprise AI infrastructure that enables autonomous agents to execute complex workflows across mission-critical software systems.

This isn't another chatbot company.

The team is building production AI agents that reason, plan, use tools, and orchestrate multi-step workflows across enterprise environments. You'll be working on the infrastructure that allows AI to reliably interact with real business systems at scale.

As one of the earliest AI engineers, you'll own core agent architecture from development through production deployment.

What you'll build

• Multi-agent AI systems powered by both open and closed-source LLMs

• Complex tool-calling and reasoning pipelines

• AI integrations with enterprise software platforms

• Training, fine-tuning, and evaluation pipelines

• AI inference infrastructure and production deployment systems

• Scalable AI platforms supporting enterprise workloads

You'll likely have experience with

• Building production AI agents from the ground up

• LLMs, agent frameworks, and tool-calling architectures

• Fine-tuning and training large language models

• AI evaluation and benchmarking

• Vector databases, RAG, and compound AI systems

• Deploying AI infrastructure across AWS, Azure, or GCP

• Shipping production AI products in fast-moving startup environments

• Founding-level ownership with significant technical influence

• Work directly with an experienced founding team

• Build foundational AI infrastructure rather than application features

• Solve challenging problems across agent orchestration, LLM infrastructure, model serving, and enterprise AI

• High autonomy, meaningful technical ownership, and early-stage equity