Engineering Manager - Platform & Data

Job Description

Job Description

At a glance

• Location: 100% remote, anywhere in the US

• Base salary: $185,000–$230,000, Position is bonus eligible.

• Team: 5 engineers today and growing; you'll partner with a systems architect as a functional counterpart

• Stack: Go (primary), TypeScript, AWS, Pulumi, PostgreSQL, DynamoDB, Databricks

• Reports to: Director of Engineering

Your way to impact

Returns are the part of online shopping shoppers say they hate most, and we're fixing that at scale. Top online retailers use Happy Returns' returns software and reverse logistics to give shoppers a genuinely easy return experience while cutting costs, retaining sales and making their supply chains more sustainable. The business is growing 25% or more year over year.

The Platform & Data team builds what the rest of engineering runs on, including Gauss, our in-house AI harness. Happy Returns is all in on Gauss. It already runs our AI-native development lifecycle: it writes tickets, scores complexity against our codebase, opens pull requests for low-complexity work, patches CVEs automatically and drafts technical designs. Next, it becomes the AI platform for the whole company, not just engineering. It's model-agnostic, runs on AWS Bedrock, and already serves Engineering, Data Science, Operations, Product, Design and CX.

That's where your team comes in. You'll own our Databricks instance and data pipeline, and build data intelligence that feeds directly into Gauss, so people across the company can use our data to make well-informed decisions. You'll also build custom RAG pipelines and vectorization flows that keep sensitive content secure, and partner with teams across the company to strengthen our future ML models.

You'll lead this team and set its direction with a systems architect as your technical partner. There's no dedicated PM: the two of you decide what to build, and you own getting it done. The team is five engineers today and will grow, and over the next few years you'll shape who joins and how the team is built. This is a management role: you're welcome to write code, but it isn't expected.

What your team owns

• Gauss and the AI-native development lifecycle built on it

• Shared services that every product team depends on

• Data workflows and reporting the business relies on

• Internal tooling that removes toil and speeds up delivery

Your day to day

• Lead and grow the team. Shape the team as it grows, and hire, coach and develop engineers through clear expectations, regular feedback, performance conversations and career planning.

• Set direction with architects. Own the team's roadmap and prioritize by business impact, technical health, risk and ROI.

• Find the highest-leverage work. Learn where other teams are blocked, where operations has gaps and where toil piles up, then turn ambiguous asks into scoped initiatives.

• Deliver what you commit to. Set owners, milestones and timelines, and raise risks, blockers and slips early.

• Make the work visible. Keep OKRs, roadmap updates, dashboards, postmortems and status updates current and useful.