Engineering Manager

HartleyCo; San Francisco (CA); On-site; USD 300,000 - 520,000; Full time

Job summary

HartleyCo in San Francisco is seeking a senior leader to build and own its AI engineering organization. You will define how production AI agents are built, grow the team, and set the foundations for three future areas: AI infrastructure, agent intelligence and evaluation, and agentic product engineering.

You will lead architecture reviews, guide product strategy with founders, recruit top engineers, and scale an organization from early-stage to high-impact.

Qualifications

• Experience leading an AI/ML engineering group (8–20 people) and hiring engineers and managers.
• Shipped a user-facing LLM or agent product into production within the past two years.
• Experience building production AI agents handling sensitive data and enterprise workflows.
• Strong Python experience; able to contribute to architecture reviews and code reviews.
• Willing to work in person in San Francisco and operate with speed and ambiguity.

Responsibilities

• Own the technical direction of the company’s AI products.
• Lead and grow the AI/ML engineering group.
• Recruit exceptional engineers, tech leads, and future managers.
• Set the architecture for production agent systems.
• Improve reliability, latency, and cost while boosting customer adoption.
• Collaborate with founders on product and company strategy.
• Maintain leadership presence in architecture reviews and experiments.
• Build the leadership structure to scale the organization.

Skills

Python

Leadership

AI/ML engineering

Recruiting

AI architecture

Job description

I’m partnering with a fast-growing, well-funded AI company to hire the leader who will build and own its AI engineering organisation.

This is not a conventional middle-management role.

You will define how the company builds production AI agents, grow the engineering team beneath you, and establish the technical and organisational foundations for three future areas:

• AI infrastructure
• Agent intelligence and evaluation
• Agentic product engineering

The company is already working with major enterprise customers and has grown revenue by approximately 10x over the past year. The AI organisation, however, is still early enough for this person to have genuine founder-level influence over its direction.

The agents being built are not lightweight productivity features or internal prototypes. They operate across complex enterprise workflows involving sensitive data, customer money, documents, voice, web interaction and connected systems.

You will own both the architecture and the product outcome.

That includes areas such as tool use, orchestration, planning, evaluations, model routing, memory, RAG, guardrails, human escalation and long-running workflows.

What you will be responsible for:

• Owning the technical direction of the company’s AI products
• Leading and growing an AI/ML engineering group
• Recruiting exceptional engineers, technical leads and future managers
• Setting the architecture for production agent systems
• Improving reliability, latency, cost, task completion and customer adoption
• Working closely with the founders on product and company strategy
• Remaining active in architecture reviews, technical decisions and experimentation
• Building the leadership structure required to scale the organisation

You are likely to be a strong fit if you:

• Currently operate as a Senior Engineering Manager, Director of Engineering, Head of AI or Head of Applied AI
• Have led an AI or ML engineering team of roughly 8 to 20 people
• Have personally recruited and built part of that team
• Have shipped a user-facing LLM or agent product into production within the past two years
• Have owned measurable product outcomes, not solely infrastructure or research
• Can lead across both the application and platform layers
• Have built enterprise B2B software involving sensitive data or consequential actions
• Are still technically credible in code and architecture reviews
• Have strong Python experience
• Are comfortable operating with speed, ambiguity and direct founder interaction
• Are willing to work in person in San Francisco

Insurance experience is useful, but it is not essential. The priority is finding someone who has built and scaled customer-facing AI agents in a demanding production environment.

The company can shape the opportunity around an Engineering Manager, Senior Engineering Manager or Director-level candidate. The defining factor will be your ability to build the team, set the technical bar and take ownership of the AI organisation.

You will work alongside an exceptional technical leadership group, including an ex-Apple AI Research CTO and an ex-Brex VP of Engineering, while retaining clear authority over the AI function.

The central opportunity is simple:

Come and build the AI organisation, rather than simply managing one that already exists.