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AI Product Engineering Lead San Francisco

San Francisco, CA, United States

Hex is changing the way people work with data. Our platform makes analytics workflows more powerful, collaborative, and shareable. Hex solves key pain points with today's data and analytics tooling, and is loved by thousands of users all over the world for the beautiful UI, new superpowers, and boundless flexibility.

We are a tight-knit crew of engineers, designers, and data aficionados. Our roadmap is full of big ideas and little details, and we would love your help bringing them to life.

Hex has raised over $100m from great VCs and angels, giving us many years of runway and the ability to pay competitive salaries, offer great benefits, and provide meaningful equity.

Large language models are unlocking new possibilities for software of all kinds – including data analytics. At Hex, we were early to incorporate powerful AI features into our product, unlocking LLM-powered workflows for thousands of users.

We’re looking for an exceptional engineering leader to level up the execution of our AI team across the stack – from partnering with research to identify the most important experiments to architecting scalable backends to shipping delightful features. This person must successfully align a team of world-class subject matter experts and drive them toward success around a unified outcome that accelerates Hex’s product strategy over the next several years.

On any given day you might find yourself:

Leading the team to deliver an industry-leading AI-assisted experience for data analytics workflows.

Developing and executing on a technical strategy for optimizing current technology in partnership with SMEs (e.g. using multiple models or deploying to different architectures) and for quickly incorporating new advancements as they arise.

Cultivating a high-output, high-vision team culture on one of the most important teams at the company.

Engaging with the AI community to maintain and extend Hex’s thought leadership and marketing presence.

Working with EPD leadership to develop future phases of AI product strategy within Hex.

This is a full-time role based out of our San Francisco office. Employees are encouraged to come into the office at least twice a week, with Tuesdays and Thursdays being our main in-person days.

About you! At least 8+ years of engineering experience, with at least 4+ in a management capacity

Strong focus on execution, with a track record of shipping complex, full-stack projects with multiple stakeholders within the context of a top-tier EPD organization.

Technical chops and desire to go deep with LLM and related technology – must be able to appropriately “nerd out,” not just in the weeds of the implementation but also in envisioning the possibilities of the future.

Strong product intuitions, particularly about users, workflows and prioritization.

Background working with research projects and understanding how to evaluate and measure their success.

Must be hands-on, e.g. reading RFCs or giving feedback on the designs, joining customer calls, and using the product frequently.

Clear, proactive communication, particularly with less technical stakeholders. This includes not just what is being built but when and why .

Inspiring and compassionate people management to lead the team to great achievements while helping them navigate the stress of working with cutting-edge technology in a rapidly changing environment.

Talent magnet: experience hiring incredible individuals with the connections in the industry to attract & sell that talent on Hex.

Familiarity with modern data technologies and the trends within the industry.

Our stack Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack.

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