Growth Platform, Marketing Engineer

Role Overview

Faire’s marketing org runs largely on systems marketing does not currently build. Audiences and attributes, campaign automation, landing pages, attribution, translation, paid feeds, monitoring and alerting: today most of it gets assembled request by request, or waits on a partner engineering pod carrying its own roadmap. The Marketing Engineer builds those systems inside marketing, on Faire’s production stack, and enables marketers to then run solo.

This is an engineering role sitting inside marketing. You will write production code across Faire’s codebase, own services end to end, take part in on-call, and put agents into marketing workflows with the evals and monitoring that make them trustworthy at scale. You will be measured on whether the marketing org gained a capability it did not have before.

The surface you own can span various disciplines: Paid media tooling and feed automation, the landing page framework, lifecycle and campaign systems, the marketing data layer, internal platform tooling, and the consumption layer for Faire’s recommendation and propensity models inside marketing surfaces are all in scope. You will help define how we work with our broader EPDD partner teams.

What you'll build first

Before you join, these problems will probably have moved, you should be comfortable with that. Below are two current problems we’re looking at solving short term:

Marketing-led landing pages. Our current marketing led landing pages workflow is slower than it should be for the blog, newsroom and content teams, and for landing page tests in lifecycle and paid we’re often spending more time talking/prioritizing experiments than building experiences for them. You will own this surface end to end, and you will own the recommendation on where it goes next: you might decide between vendor vs. in-house solution, or build a self-serve, agentic landing page service. The outcome is simple, better, faster landing pages, more self serve, and happy partner teams.

Self-serve audiences and attributes. Our partner teams currently go through us for Audience syncing with paid platforms and marketing led lifecycle. We think this should be a self service capability available to our marketers: whether that's a vendor or in-house, how the data contract gets enforced in code, and what the self-serve layer looks like are all open questions this person will answer to ensure we reach the right person at the right time with the right message.

Other projects on our radar: a learning loop for generative assets in ad campaigns, improving infra behind core intelligence feeds powering our paid campaigns, real-time recommendation management across lifecycle and paid, and more.

How we work

• Own services end to end. Design, build, review, deploy, monitor.
• Ship in Faire's production codebase, to Faire's engineering standards, with code review by engineers.
• Sit with lifecycle, paid, brand and product marketing rather than behind a ticket queue. Find the pattern behind the requests, then decide what to build so they stop arriving.
• Put agents into the patterned majority of the queue, with an eval harness, monitoring and a defined failure mode before anything reaches a customer.
• Turn ambiguous asks into a scoped, prioritized plan, and communicate tradeoffs and progress to non-technical stakeholders.

Qualifications

Required

• 4+ years shipping and owning production software, in or adjacent to a marketing, growth or GTM organization.
• You'll work in Faire's production codebase. Faire’s stack is Kotlin, Java, JUnit, Hibernate, Guice and Jersey, React and Next.js, HTTP, JSON and Protocol Buffers, MySQL and CockroachDB, on AWS.
• SQL and enough comfort in the warehouse to instrument what matters and decide what to build next from the data.
• Depth in at least one marketing platform: a CDP or ESP (Braze, Iterable, Segment, Hightouch), an attribution or analytics platform, a CMS, or an ad platform API.
• Daily use of AI coding agents, plus experience putting LLMs into production systems with evals, monitoring and a defined failure mode.
• A track record of owning a system end to end, including the on-call, and shipping it to non-technical users who then operated it without you.

Preferred

• Marketplace or two-sided e-commerce experience.
• Production experience with Kotlin or Java on the backend and JavaScript or TypeScript with React or Next.js on the frontend.
• Having replaced a martech vendor with an in-house build, and being able to say what it cost.
• Braze, Hightouch, Google Ads, Meta.

Salary Range

Toronto: the pay range for this role is $140,000 to $192,500 per year.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.