AI/ML Engineer — Production Agent Architect

Harnham; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Harnham is seeking a senior AI/ML software engineer to own the intelligence layer of an AI-native data platform for enterprise clients. You will architect multi-step agents, design RAG pipelines, and drive production-grade AI features from model selection to output validation.

Ideal candidates have 4–6+ years of software engineering with deep AI/ML experience, strong Python skills, and hands-on work with LLMs, vector databases, and knowledge graphs.

Qualifications

• 4–6+ years of software engineering experience with meaningful AI/ML depth.
• Proven experience building and shipping AI agents or coding agents in production.
• Strong Python skills with hands-on experience across RAG, vector databases, and knowledge graphs.
• Experience with LLM APIs, prompt engineering, fine-tuning, and structured outputs in production.
• Familiarity with AWS and Kubernetes for production AI deployment.

Responsibilities

• Architect multi-step AI agents end-to-end, covering problem decomposition, context retrieval, error recovery, and output quality.
• Own RAG pipelines, vector and graph-based retrieval systems, and knowledge representations that let agents reason accurately over complex enterprise data.
• Build the AI layer behind the platform's core code generation capability, from prompt design and model selection through to fine-tuning and output validation.
• Make production AI work at scale, balancing latency, throughput, and observability, and knowing when to optimize a model versus restructure a system.
• Think in failure modes and evaluation strategy, not capability demos, and own the improvement loop.

Skills

Python

AI/ML depth

AI agents in production

LLM APIs

Prompt engineering

AWS

Kubernetes

Tools

Databricks

Snowflake

BigQuery

Spark

Job description

Harnham is seeking a senior AI/ML software engineer to own the intelligence layer of an AI-native data platform for enterprise clients. You will architect multi-step agents, design RAG pipelines, and drive production-grade AI features from model selection to output validation.

Ideal candidates have 4–6+ years of software engineering with deep AI/ML experience, strong Python skills, and hands-on work with LLMs, vector databases, and knowledge graphs.