Senior Product Engineer (Full-Stack & AI)

Someone hands you a Figma file. You ship it.

A buyer wants to search tens of thousands of hours of footage for "people cooking, filmed from above, in Tamil" and get back clips cleared for training. The design is in Figma, the agents behind it need building, and the infrastructure to run it at scale is yours to define. You take it from there.

The Senior Product Engineer takes a feature from Figma to production on their own: a pixel-perfect Next.js front end, the TypeScript services behind it, the AI agents that power it, and the AWS infrastructure it runs on. We're a small team, so you'll own whole slices of the product and have a real say in how we build.

We're looking for someone who cares about craft, would rather ship than debate, and considers an AI feature without evals to be a demo.

About ContentX Labs

ContentX Labs is the rights-cleared data foundation for real-world AI. We supply licensed video to teams building generative video, avatars, robotics and other AI systems that need to learn how the world looks, moves and sounds. The source material spans more than 100 countries and 90 languages, from scripted and documentary to sport.

Our position is simple: ambiguous rights don't stay with the supplier, they follow the model. So we clear rights before material enters the pipeline, not after.

The platform makes that work. It ingests, structures and enriches video with scene-level metadata and clear usage rights, so the material is ready for training, fine-tuning and evaluation when it arrives. That platform is what you'll build.

What you'll actually do

• Build features end to end.

  TypeScript throughout, from data model and API to UI.

• Turn Figma into product.

  Build pixel-perfect, responsive, accessible interfaces in Next.js and React, using CSS Modules and Tailwind where each fits best.

• Handle state properly.

  Own data fetching and client state with TanStack Query, getting caching, optimistic updates, pagination and error states right first time rather than eventually.

• Build the AI harness.

  Agent loops, tool calling, structured outputs, retrieval, evals, guardrails, tracing and cost control: the parts that make natural-language search over video actually work.

• Run what you build.

  On AWS, defined in Terraform and reviewed like any other code.

• Keep delivery fast and safe.

  CI/CD on GitHub Actions covering tests, previews, automated deploys and rollbacks.

• Make the calls.

  Take pragmatic architecture decisions, write them down, and help raise the bar on code review and engineering practice.

Who you'll work with

You sit in the product team, alongside analysis, QA and the people who deliver what the platform produces to buyers.

Product

Sets the problem and the design. You decide how it's built, and push back when the design and reality disagree.

CTO and engineering

Review your architecture and code, and share ownership of the platform and infrastructure.

QA and delivery

Check what ships against real buyer deliveries, so you hear quickly when something doesn't hold up.

Analysis and scrum

Run the sprint rhythm and the numbers, so priorities are visible and progress is measured.

Data supply and sales

Bring the buyer requirements that shape what the platform needs to do next.

The rhythm is a light sprint cycle. Everything else is you getting on with it.

Who you are

• Full-stack in TypeScript and JavaScript.

  At least 5 years shipping production web apps across front end and back end (Node.js).

• Deep in Next.js and React.

  Server and client components, rendering strategies, performance and accessibility.

• Fluent with TanStack Query.

  You know how to structure query keys, invalidation and mutations in a real app.

• Precise with styling.

  Fluent in CSS Modules and Tailwind, with a track record of pixel-perfect implementation from Figma.

• Experienced with LLMs in production.

  You've built LLM-powered features that real users rely on, on a modern stack. You care about evals, not vibes.

• At home on AWS.

  Comfortable with the core services (Lambda or ECS, S3, RDS or DynamoDB, IAM, CloudWatch) and with debugging in production.

• Practised in Terraform.

  You write and review infrastructure as code: modules, state, environments.

• A pipeline builder.

  You build and maintain CI/CD on GitHub Actions rather than just using it.

• An owner who writes things down.

  You work well remotely and communicate clearly and asynchronously in English.

Helpful but not essential:

Python, especially for data processing or evals; experience with video, media or large-dataset pipelines; time at an early-stage startup or as a founding engineer.

This is a senior role, so the list above is the bar, not a wish list. If you meet it and the idea of owning a slice of product outright appeals, read on.

How we'll know it's working

The headline measure is features in production that buyers use. Tickets closed don't count on their own.

• First 30 days:

  set up, a first change shipped to production, and a working knowledge of where the bodies are buried in the codebase.

• First 90 days:

  a user-facing feature shipped to production and one piece of our infrastructure owned in Terraform.

• Ongoing:

  faster and safer releases, AI features with evals behind them, and fewer surprises in production.

What this role isn't

• Not a ticket-taker.

  You'll get problems and designs, and you're expected to have opinions on both.

• Not front end or back end.

  It's both, plus the infrastructure underneath.

• Not an AI demo factory.

  If a feature can't be evaluated, monitored and costed, it isn't finished.