Partner Engineer

About the Role

Uber’s delivery ecosystem is powered by deep technical integrations with an ever-growing network of external partners. As a Portfolio Partner Engineer, you’ll be embedded in the restaurant tech ecosystem-working with POS, middleware, ordering, and operational platforms-to help partners build on Uber’s platform and scale reliably. You’ll operate in an “embedded” model: equal parts architecture + hands-on execution, with outsized impact on integration speed, quality, and day-2 reliability.

What the Candidate Will Need / Bonus Points

• Own technical delivery for a set of restaurant tech partners: scope, design, build, launch, and operate integrations end-to-end.
• Collaborate with partner engineers to implement Uber APIs/webhooks correctly and drive launch readiness (testing, rollback plans, monitoring).
• Build durable integration patterns (templates, libraries, runbooks) to reduce one-off work and accelerate future launches.
• Triage and resolve complex production issues across partner + Uber systems; improve observability and prevent repeat incidents.
• Partner tightly with the UK-based Restaurant Tech Partner Engineering Lead and cross-functional stakeholders across EMEA (Product/Platform/BD/Ops) to translate ecosystem needs into clear technical plans.

---- Basic Qualifications ----

• Hands-on engineering experience shipping production integrations (APIs, webhooks/events, SDKs, distributed systems) and strong debugging/troubleshooting ability.
• Proficiency in at least one modern language (Python, Java, Go, Node.js) with the ability to write and review production-quality code.
• Experience working directly with external technical stakeholders (partners/customers) to deliver implementations through ambiguity (technical scoping, timelines, launch readiness).

---- Preferred Qualifications ----

• Experience with restaurant technology (POS, KDS/OMS, menu/catalog sync, payment flows, delivery aggregation/middleware) or adjacent commerce ecosystems.
• Strong systems instincts around reliability, observability, and scale (idempotency, retries, rate limits, monitoring, incident response).
• Data fluency: SQL + analytics to diagnose integration health and drive prioritization (failure taxonomy, SLA/SLO thinking).
• Track record building reusable integration assets (reference implementations, test harnesses, partner onboarding docs, automation/tooling).