Backend Engineer - Case Management

Our Global Structure

Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team.

We are looking for a Senior Backend Engineer to help build and evolve our new Common case-management system, which powers support-case handling across DoorDash, Wolt, and Deliveroo.

You will own significant end-to-end initiatives across our backend services: case lifecycle, routing and assignment, queue management, case evidence and history, and migration from legacy systems. This is a hands-on role for someone who can turn ambiguous customer and operational problems into durable technical solutions, coordinate other engineers, and set the standard for reliability and craftsmanship on the team.

• Lead one or more project-level Case Management initiatives, on your own or by guiding a group of engineers, from discovery and design through rollout, measurement, and operational ownership.
• Design and build scalable backend services and APIs for case creation, routing, assignment, transfers, audit history, notes, attachments, and queue-management workflows.
• Help deliver feature parity with legacy platforms while safely migrating traffic across DoorDash, Wolt, and Deliveroo.
• Make and own most technical decisions within your scope. Write project-level design documents covering how sub-features interact, identify dependencies and risks, and break work into parallelizable delivery plans.
• Scope ambiguous customer and operational problems, weigh long-term against short-term trade-offs, and design durable solutions.
• Partner with Product, Operations, Support, Data, and other engineering teams to define the right problems. Shape the team roadmap through prototypes, data analysis, project proposals, and backlog prioritization.
• Run the coordination a project needs, such as status updates and dependency tracking, and escalate early to keep delivery on time.
• Enforce team-wide quality objectives: lead design reviews, calibrate quality metrics, and improve logging, monitoring, alerting, and escalation policies.
• Serve as first responder or incident commander, model good incident practice, and turn what you learn into playbooks and backlog work.
• Introduce and guide AI best practices for the team, including evals, data privacy, and review of AI-generated code, and take part in AI-powered projects when they are central to the product.
• Design reusable, self-serviceable solutions, and consider cost efficiency, including compute and AI costs, in key designs.
• Mentor engineers through code reviews, design guidance, tech talks, and constructive feedback. Interview candidates, join sell calls, and take part in hiring events when the team needs them.
• Delivers a major Case Management initiative with clear technical ownership, predictable execution, and measurable customer or business impact.
• Improves the reliability, maintainability, and cost efficiency of the Common system while enabling safe migration from legacy case-management systems.
• Helps move support traffic onto the Common system without reducing case-resolution quality.
• Builds solutions that other engineers and operators can confidently reuse and operate.
• Acts as a technical leader within the team: unblocks peers and partner teams, improves engineering decisions, influences the roadmap, and strengthens cross-functional execution.

• Strong backend engineering experience, including designing and operating backend services, APIs, asynchronous workflows, and data models at meaningful scale.
• Proficiency in at least one modern backend language, and a record of writing exemplary code for the core functionality of key components.
• Demonstrated ownership of complex, customer-facing or operations-critical projects from technical design through production rollout.
• Experience breaking projects into parallelizable work, identifying dependencies and risks, and giving accurate estimates for yourself and others.
• Hands-on experience using AI development tools to improve productivity, while validating generated output for correctness, security, privacy, maintainability, and reliability.
• Strong product judgment: the ability to turn ambiguous workflows and user needs into simple, maintainable technical solutions.
• Proven ability to collaborate across functions, bring the right stakeholders into decisions at the right time, and explain trade-offs clearly to technical and non-technical audiences.
• Strong engineering craft: testing, code review, observability, incident response, security, and operational readiness, with experience designing for reliability.
• Comfort working on systems with high correctness and auditability requirements, including traceability of decisions and changes.
• A mentoring mindset and a record of raising team-wide engineering standards.
• Go experience.
• Experience with migration from legacy systems, gradual rollouts, traffic shadowing, and feature-parity programs.
• Experience supporting internal tools or operational user interfaces from the backend side.
• Experience with high-volume, multi-region, or multi-tenant systems.
• Experience as an incident commander or in running an on-call rotation.
• Experience building AI-powered features, including evaluation of model output.