Staff & Principal AI/ML Engineer

Harnham; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Harnham partners with a high-growth AI-native data infrastructure startup to lead the technical direction of AI agents and retrieval systems. You will own architecture, evaluation strategy, and production-grade codegen capabilities, shaping how AI features are built at scale.

You'll guide multi-step agent design, mentor engineers, and drive complex initiatives from design through production in an environment with significant ownership and ambiguity.

Qualifications

• 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 production.

Responsibilities

• Set technical direction across multi-step agent architecture, RAG pipelines, and knowledge retrieval systems.
• Own the AI behind the platform's core code generation capability, from prompt design 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.

Skills

AI leadership

Python

Architectural decisions

Problem solving

Tools

Neo4j

AWS

Kubernetes

Vector databases

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 production
• Experience with AWS and Kubernetes, and comfort operating across the full AI development lifecycleExperience 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.