AI Engineer - GTM

Tracksuit exists to help marketers prove their brand building is working. We give teams the data they need to make smarter decisions, convince stakeholders, defend budgets, and track their progress. The brand tracking industry is dominated by 100-page reports, static data and big price-tags. We're doing things differently by being built for the modern marketer: always-on, accessible, and approachable.
We're now tracking more than 16,000 brands across 25 countries globally. With offices in Auckland, Sydney, London and New York City, we're scaling fast with a brilliant team of collaborative and ambitious humans. Our culture is defined by "high care, high performance". We strive to be the best and look after each other while we do it.

We're committed to a diverse, inclusive workplace where everyone can be themselves. We value a unique perspective, varied experience and a growth mindset over ticking every box. If this role excites you but you don't match every point, please still get in touch and apply.

We're hiring an engineer to join our AI Systems team and build for our go-to-market (GTM) teams. You'll make the agents, apps and integrations that Sales, Customer Success, Marketing and Partnerships use every day.

This is an engineering role, and a technically strong one. You'll write production code, own what you ship and keep it running. It also isn't a standard engineering job. What we build has to flex to the world of GTM, and the mix changes as the business does. If you're comfortable in the uncomfortable, you'll love it. If you've mostly worked in RevOps or with no-code tools, this probably isn't the right fit.

There's no backlog waiting for you. You'll define what good looks like, work with GTM leaders to decide where we should focus our efforts, then build it and ship it. Self-starters are key. We'll give you context and access to the people you need, and trust you to run with it.

• Build AI agents for GTM work. Account research, meeting prep and follow-up, proposal and RFP drafting, lead routing and renewal risk signals, with human review and approval steps where they're needed.

• Ship internal tools. Own full-stack apps for Sales, CS and Marketing from prototype to launch, then keep improving them.

• Build the plumbing. Create MCP servers and integrations, and keep an eye on what our AI usage costs.

• Work closely with the GTM teams. Set the standard for what good looks like, and help our other GTM engineers get up to speed so we ship at pace.

• Measure what you ship. Add tracking to your tools, write evals for anything that uses an LLM, and check whether what you built gets used and moves pipeline or retention.

• Own engineering and security standards. Write the conventions, review practices and docs that let others contribute safely to a shared codebase, and build with permissions, privacy and security in mind from the start.

• You're an engineer first. You've built AI projects that people use in production. You made the technical calls, wrote much of the code and kept them running after launch.

• You're comfortable without a spec. You can take a vague request from a non-technical teammate, work out what needs building and get it live without someone writing tickets for you.

• You've shipped LLM work in production. Tool use, agents, MCP, context engineering and evals. When a model misbehaves, you read the transcripts to work out why.

• You've got product and commercial judgement. You care whether people use what you build and whether it helps the business.

• You enjoy helping others level up. You're happy to pair with, review and teach teammates who are earlier on the path to becoming GTM engineers.

• Autonomy that's rare in engineering. You'll decide what to build and how, with real trust behind you.

• A small team that moves fast. Few layers, quick decisions, and things get shipped.

• A front-row seat to a new space. You'll work in a very new, fast-growing area and see a lot of it.