Staff & Principal AI/ML Engineer

Harnham; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Harnham in San Francisco seeks a senior technical leader to shape the architecture of AI agents and data infrastructure. You will define how multi-step agents, RAG pipelines, and knowledge retrieval systems are designed, built, and evaluated across the platform.

You will own the AI coding capability from prompts to validation, mentor engineers, and drive production-grade decisions as the company scales toward its next funding round.

Qualifications

• 8+ years of software engineering with AI/ML leadership.
• Experience owning and shipping AI agents in production at scale.
• Strong Python with RAG, vector DBs, and knowledge graphs (Neo4j).
• Ability to make architectural decisions under uncertainty and ship to production.
• Experience with AWS, Kubernetes, and full AI development lifecycle.
• Experience with Databricks, Snowflake, BigQuery, Spark; Scala/Go bonus.

Responsibilities

• Set technical direction for multi-step agent architectures, RAG pipelines, and retrieval systems.
• Own the platform's AI coding capability from prompt design to large-scale validation.
• Lead large initiatives end-to-end with minimal direction.
• Shape production AI with standards for evaluation, observability, and reliability.
• Influence architectural decisions and mentor engineers across the org.

Skills

Python

AI/ML leadership

RAG pipelines

Vector databases

Knowledge graphs (Neo4j)

AWS

Kubernetes

Databricks

Snowflake

BigQuery

Spark

Scala

Go

Tools

Neo4j

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 in senior technical leadership to define how AI gets built across the company.

This is a role for someone who sets technical direction, not just executes it. You'll shape agent architecture, evaluation strategy, and retrieval systems at the core of the platform, leading large-scale initiatives from design through to production with real ownership over outcomes. The scope is intentionally open-ended, and strong engineers have enormous leverage here.

What You'll Do

• Set technical direction across multi-step agent architecture, RAG pipelines, and knowledge retrieval systems, making the calls on agent design, model selection, and build vs. buy
• Own the AI behind the platform's core code generation capability, from prompt design and fine-tuning through to output validation at scale
• Lead large, complex initiatives end-to-end with minimal direction, defining the problem as much as the solution
• Shape how production AI gets built across the team, establishing standards for evaluation, observability, and reliability
• Influence architectural decisions across the broader engineering organisation and mentor engineers at all levels

Requirements

• 8+ years of software engineering experience with significant AI/ML depth and a track record of technical leadership
• Demonstrated experience owning and shipping AI agents or coding agents in production at scale
• Strong Python skills with deep hands-on experience across RAG, vector databases, and knowledge graphs (Neo4j)
• Ability to make architectural decisions under uncertainty and drive them through to productionExperience with AWS and Kubernetes, and comfort operating across the full AI development lifecycle
• Experience with data platforms such as Databricks, Snowflake, BigQuery, or Spark is a strong plus
• Scala or Go experience is a bonus

If you're a technical leader who defines problems as much as you solve them, thrives in ambiguity, and wants to shape how AI is built at a company scaling toward its next funding round, this is the opportunity.