AI Agent Builder

Harrison Clarke; Palo Alto (CA); Vor Ort; USD 180.000 - 240.000; Vollzeit

Zusammenfassung

Harrison Clarke partners with a Palo Alto-based seed-stage AI startup to hire an AI Agent Engineer. You will design multi-step, tool-using agents and own core framework decisions.

You’ll work on RAG pipelines, memory systems, guardrails, and performance optimization across cloud infrastructure. This hands-on role offers real ownership in a fast-moving, small team.

Qualifikationen

• Production experience with LLM-based systems.
• Experience with RAG, embeddings, and vector databases.
• Familiarity with agent frameworks (LangGraph, LangChain, AutoGen).
• Experience with tool-calling, API orchestration, and multi-step reasoning workflows.
• Strong Python skills and cloud deployment experience.

Aufgaben

• Design and build multi-step, tool-using AI agents.
• Architect RAG pipelines and memory systems.
• Implement planning, execution, and verification loops.
• Develop guardrails and reliability mechanisms for enterprise environments.
• Optimize inference performance and latency.
• Deploy production systems across modern cloud infrastructure.

Kenntnisse

LLM-powered systems

RAG & embeddings

Tool-calling & API orchestration

Python

Cloud deployment

Team collaboration

Tools

LangGraph

LangChain

AutoGen

Vector databases

Jobbeschreibung

AI Agent Engineer | Palo Alto | Seed-Stage, VC-Backed

We are working with a well-funded, early-stage AI startup based in Palo Alto that is building next-generation enterprise AI agents capable of automating complex, multi-step business workflows.

This is not a chatbot role. The team is focused on designing reliable, production-grade agent systems that can reason, retrieve context, call tools, and execute tasks safely across enterprise platforms such as SAP, Salesforce, and Workday.

Backed by top-tier institutional investors and led by founders with deep AI research and enterprise systems experience, the company is assembling a small, high-caliber engineering team to define what scalable, real-world agent architecture looks like.

The Role

As an AI Agent Engineer, you will:

• Design and build multi-step, tool-using AI agents
• Architect RAG pipelines and memory systems
• Implement planning, execution, and verification loops
• Develop guardrails and reliability mechanisms for enterprise environments
• Optimize inference performance and latency
• Deploy production systems across modern cloud infrastructure

This is a hands-on engineering role with real ownership. Early hires will shape the core agent framework and system design.

What They\'re Looking For

• Strong experience building LLM-powered systems in production
• Experience with RAG, embeddings, and vector databases
• Familiarity with agent frameworks such as LangGraph, LangChain, AutoGen, or similar
• Experience with tool-calling, API orchestration, and multi-step reasoning workflows
• Strong Python skills and cloud deployment experience
• Comfort operating in small, fast-moving teams

Ideal candidates have built more than just LLM demos. We are looking for engineers who understand how agents fail, how to design around those failures, and how to ship reliable systems.

Why This Opportunity

• Seed-stage but institutionally backed
• Real ownership and architectural influence
• Focused on meaningful enterprise automation problems
• Bay Area based

If you are interested in building real AI agents that execute work rather than generate text, I would be happy to share more details confidentially.