AI/ML Engineer

Harnham; San Francisco (CA); Hybrid; USD 315,000 - 385,000; Full time

Job summary

Harnham, a Bay Area–based data and AI solutions provider, seeks an AI/ML Engineer (All Levels) to architect end-to-end AI agents and RAG pipelines. You will shape the intelligence layer of a rapidly growing platform, making architectural decisions around model selection, fine-tuning, and evaluation while shipping directly to customers.

The role emphasizes ownership, production readiness, and collaboration with teams building AI-native data infrastructure for Fortune 500 enterprises.

Qualifications

• 4-6+ years of software engineering with meaningful AI/ML depth.
• Proven experience building and shipping AI agents in production.
• Strong Python skills with RAG, vector databases, and knowledge graphs.
• Experience with LLM APIs, prompt engineering, and production-grade outputs.
• Familiarity with AWS and Kubernetes for production AI deployment.
• Experience with data platforms such as Databricks, Snowflake, BigQuery, or Spark is a strong bonus.
• Scale or Go experience is a bonus.

Responsibilities

• Architect multi-step AI agents end-to-end, including problem decomposition and context retrieval.
• Own RAG pipelines, vector/graph retrieval systems, and knowledge representations for enterprise data.
• Build the AI layer behind the platform’s code generation capability from prompts to fine-tuning.
• Ensure production AI operates at scale with balanced latency and observability.
• Think in failure modes and evaluation strategy; own the improvement loop.

Skills

Python

AI/ML

LLM APIs

AWS

Kubernetes

RAG & vector DBs

Knowledge graphs

Go

Tools

Databricks

Snowflake

BigQuery

Spark

Job description

Title: AI/ML Engineer (All Levels)

Location: Bay Area (Hybrid)

Compensation: Up to $350,000 + Equity

We’re partnered with a well‑funded, high‑growth Series B startup building the next generation of AI‑native data infrastructure for Fortune 500 enterprises. With 3.5x revenue growth in FY’24 and 160% net revenue retention, they’re scaling fast and investing heavily in the AI engineering team that powers their core product.

This is a high-impact role where you’ll own the intelligence layer of the platform, making real architectural decisions around agent design, model selection, and evaluation strategy. Everything you build ships directly to customers; this is not a POC or internal tooling team.

What You’ll Do

• 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

Requirements

• 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
• Experience with data platforms such as Databricks, Snowflake, BigQuery, or Spark is a strong bonus
• Scale or Go experience is a bonus

If you’re a builder who thinks in failure modes, owns what you ship, and thrives in environments where last year’s best practice is already obsolete, this is a rare opportunity to have direct leverage on a product used by some of the world’s largest enterprises.