Director of Engineering, Logistics

About The Team

DoorDash is seeking a seasoned Engineering Director to lead our Logistics Org. You’ll lead a multi-disciplinary organization of 100+ engineers (Backend, Mobile, Machine Learning, and Operations Research) to architect the intelligent, real-time systems that comprise the "brain" of our fulfillment engine. This organization builds the optimization engines and high-throughput AI platforms that guide millions of Dashers and deploy tens of millions of dollars in real-time.

This team sits at the heart of DoorDash’s fulfillment ecosystem, powering the delivery and courier data that drives our logistics engine. We build the foundational models and workflows that enable our customer teams (Order, Shopping, and beyond) to build extensible solutions on top of the platform.

About The Role

DoorDash is seeking a Director of Engineering with a deep background in Large-Scale Systems, Machine Learning, and Mathematical Optimization to lead our Logistics team in San Francisco. In this role, you are the architect of our three-sided marketplace. You will oversee the development of the core fulfillment platforms responsible for real-time dispatching, dynamic pricing task-allocation, ETAs and supply-demand balancing.

This is a unique opportunity to marry complex algorithmic research with "five-nines" platform reliability. We are also looking for a leader who is deeply bought into the transformative potential of AI; someone who sees large language models, foundation models, and world model architectures not as adjacent curiosities but as core primitives for reimagining how logistics systems learn, plan, and adapt at scale. You’re excited about this opportunity because you will… Define the AI Platform Vision: Drive the engineering strategy, transitioning bespoke algorithmic solutions into a unified, scalable AI/Optimization platform.

Architect Real-Time Decision Engines: Lead the development of systems that solve complex combinatorial problems (VRP, assignment, pricing) in milliseconds at massive scale. Build "Production-Grade" ML: Ensure that our machine learning models aren't just accurate in a notebook, but are backed by robust feature stores, low-latency serving infrastructure, and rigorous backtesting frameworks. Scale High-Throughput Infrastructure: Evolve the underlying distributed systems to handle exponential growth, ensuring the platform remains stable under the load of millions of concurrent requests.

Cross-Functional Leadership: Partner with Business, Product, and Data Science to turn high-level marketplace objectives into technical roadmaps that balance long-term platform health with immediate business impact. Champion Engineering Excellence: Scale the organization by mentoring high-growth leaders and attracting world-class talent in the fields of Distributed Systems and Applied AI. D.

in Computer Science or equivalent. An AI-native leadership mindset.

of AI - including foundation models and world model approaches - in transforming logistics. You've thought seriously about how these technologies can move logistics beyond hand-tuned rules toward systems that learn, adapt, and generalize, and you know how to rally an engineering org around that vision without losing sight of production reliability and business impact. 12+ years of software engineering experience, including 7+ years leading engineering managers and multiple teams.

Experience building and scaling high-performing engineering organizations. You've led multiple teams through hypergrowth, re-orgs, developed managers into leaders, and created leverage through systems and strategy. A strategic mindset that shapes technical direction.

You define multi-quarter roadmaps, make high-stakes architectural decisions at scale, and translate ambiguous business problems into clear technical strategies.