Founding Head of Engineering

Talent

5d • Remote

About The Position

We're building a product where AI isn't a feature bolted on the side — it's woven through every layer, from how the product is generated to how users experience it. We're looking for a Founding Head of Engineering to take technical ownership of what's been built so far and lead it through its next chapters: shipping, scaling, and growing the team behind it. This is a high-leverage role with the autonomy and influence that come with being the founding engineer on a new product. You'll set the technical direction, make the architectural calls that matter, and become the person who hires and mentors the engineers who join after you. The team will stay small on purpose, and that's the point. We're not hiring someone to manage a hundred engineers. We're hiring someone who has done that, knows exactly what they'd never repeat, and now wants to build something tight and excellent with their own hands. The moat here is the culture of the engineering team, not any single feature — the space moves too fast for a feature to stay a moat. What compounds is how the engineers think, ship, and raise the bar on each other. You set that. The first handful of people you hire and the standard you hold them to will matter more than any architecture diagram. We want someone who treats the engineering culture as something they are building, alongside the software.

Requirements

• You've led engineering teams at real scale, and you're deliberately choosing to go small and hands-on now. The pull toward a tiny AI-native team where you're back in the code is the point, not a compromise.
• Founding or first-few engineer at a venture-backed AI startup. You've felt what it's like to operate without a playbook.
• Shipped agentic LLM systems to paying enterprise customers — not prototypes, not internal demos. Real users, real workflows, real escalation paths.
• Made the "rewrite vs. keep" call on someone else's in-flight codebase — and were right about it.
• Hired and mentored engineers. Even informally. You can articulate what makes a strong early-stage technical bar.
• You've set an engineering culture before, on purpose, and can point to teams that were measurably better because you ran them.
• Cleared a regulated procurement gate in production — security review, bias audit, compliance certification, or equivalent.
• Full-stack capable. You move comfortably across backend, frontend, and infra; you know when to specialize and when to glue things together.
• Comfortable in a conversation with a Head of Recruiting. You can translate between the customer and the codebase in the same hour.
• Excellent communicator who can translate between technical and non-technical audiences.

Nice To Haves

• Experience with Python.
• Experience with Temporal (or comparable workflow orchestration platforms).
• Direct production experience with Anthropic, OpenAI, or other major model providers — including migrating between them.
• Built evals customers actually trust, not vanity dashboards.
• Background contributing to or shipping AI-native products in regulated industries (healthcare, financial services, hiring).
• Open source contributions or technical writing in the AI / ML space.

Responsibilities

• Take full ownership of the product's codebase, architecture, and roadmap.
• Lead engineering for our AI-native product — own the technical direction end-to-end.
• Build and integrate AI capabilities deeply into the product, including LLM-based generation, agentic workflows, evals, and the infrastructure that supports them in production.
• Ship fast. Take features from rough idea to in front of users with strong instincts for what to build, what to cut, and what to defer.
• Make the foundational technical decisions — model selection, evaluation frameworks, data and inference pipelines, observability, and the trade-offs between latency, cost, and quality.
• Build the eval and observability layer that makes agentic decisions defensible to customer security, procurement, and legal teams.
• Sit in customer calls weekly. Translate customer signal directly into product.
• Recruit, interview, and hire the engineering team as we scale. You'll define the bar, run the loops, and shape the engineering culture from day one.
• Set and protect the engineering culture as a deliverable, not a byproduct: how we ship, how we review, how we handle failure, how we keep velocity high without breaking trust with enterprise customers.
• Mentor and lead future hires, setting standards for code quality, review, and shipping cadence.
• Partner closely with product and leadership on strategy, prioritization, and customer feedback loops.

Benefits

• The salary range listed in this posting is provided for informational purposes only. Final compensation will be determined based on a number of factors, including the candidate's skills, qualifications, and experience, as well as internal equity, market conditions, and business needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed