AI/ML Engineer

Harnham; San Francisco (CA); On-site; USD 170,000 - 240,000; Full time

Job summary

Harnham is seeking an experienced AI/ML software engineer to own the intelligence layer of our platform. You will architect multi-step AI agents, design RAG pipelines, and oversee production-grade deployment choices that impact enterprise customers.

The role emphasizes building scalable AI systems, fine-tuning models, prompt engineering, and ensuring robust evaluation. You’ll collaborate with data and product teams to ship high-impact features at scale.

Qualifications

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

Responsibilities

• Architect multi-step AI agents end-to-end, including problem decomposition, context retrieval, error handling and output quality.
• Own RAG pipelines, vector databases and knowledge representations for enterprise data.
• Build the AI layer behind the platform's core code generation, from prompts to fine-tuning and validation.
• Ensure production AI works at scale, balancing latency, throughput and observability.
• Think in failure modes, define evaluation strategies, and drive the improvement loop.

Skills

AI/ML depth

AI agents in prod

Python

LLM APIs

Prompt engineering

Education

Bachelor's degree in CS or related field

Tools

RAG pipelines

Vector databases

Knowledge graphs

Databricks

Snowflake

BigQuery

Spark

Go

Job description

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.