Staff Software Engineer, Fullstack (Groups Shopping Team) - Engine

Your Mission

You will be the senior technical leader for Groups Shopping at Engine — the team that owns how group travel organizers discover and select hotels. We are building a world class travel shopping experience, and improving our property-ranking system to better understand what an organizer is looking for. You will help drive that work, set the technical bar, and make sure we ship with high quality.

This role exists to push three things forward:

1. Property ranking that earns its weight. Hotel discovery is the highest-leverage moment in the group booking funnel and historically the place where ranking has been least intelligent. Optimizing how we score, sort, and present properties — using a mix of behavioral data, response signals, fit signals, and LLM reasoning — is core to what this team is being asked to do.
2. Step-change scale. Groups is heading toward an order-of-magnitude increase in volume. The systems we build this year have to deliver conversion gains that compound, hold up under multiples of today's load, and not get undone by the operational drag of fast growth.
3. AI inside the product. The most interesting UX advances in Groups travel right now come from putting AI directly in the organizer's hands — embedded assistance that helps them search, compare, and decide without leaving the flow. You will help define and ship the surfaces where this happens, including the seam between the product and the AI tools that drive it

What You'll Own

• Architecture for Groups Shopping. The hotel discovery, scoring, and selection surfaces — and the integration points where ranking, search, and AI in the product come together.
• The technical bar. You are the gate for quality on this team. Code review on hard PRs, design review on every meaningful change, "is this the right abstraction" calls before they become permanent.
• AI in the workflow. Both the agentic coding posture inside the team (we expect every engineer to be using Claude Code, Cursor, or equivalent every day) and the agentic product surfaces — tool definitions for AI surfaces in the product, prompt and skill design where needed, scoping which problems the LLM should and shouldn't own.
• AWS and CI/CD. Our backend runs on AWS — services, queues, data pipelines, ECS/Lambda where appropriate. You will own non-trivial infrastructure decisions and be the person who makes our deploy and CI story sharper.
• Mentorship and unblocking. Pairing with senior engineers, running design reviews, writing the docs that make the next person's job easier, being the named contact when another team needs a Groups Shopping perspective.

What We're Looking For

Must-haves

• TypeScript and Node in production at scale. We are open to other modern backend languages on your résumé, but our stack is TS/Node and you should be ready to be productive in it within weeks.
• AI-first as a daily practice, not a talking point. You are actively using agentic coding tools (Claude Code, Cursor) and you have a point of view on where they help, where they hurt, and how to set the team's defaults. We will ask you to walk us through a real example of how you use them.
• Deep AWS and CI/CD. Not "I've used Lambda before." Closer to: you can debug a misbehaving ECS service in production, you have opinions on IaC, and you can sharpen a slow CI pipeline.
• Cross-functional, multi-level communication. You can write a one-page tech doc that a PM can review, run a design discussion with three other staff engineers, and walk a senior leader through a trade-off without a slide deck.
• Comfort leading and running a team. Not as a manager — as the most senior engineer the team leans on for direction, sequencing, and quality. You've done this before and it's a part of the job you actually like.

Nice-to-haves

• Deep TypeScript / Node — internals, performance, type-system fluency.
• Product experience — you can wear a PM hat for an afternoon and think from the customer's seat.
• Travel, hospitality, marketplace background.
• React Native familiarity