About the Role

You'll work directly with our cofounder with direct ownership over the direction of AI research at DoorDash. In this role you will develop realistic agent environments and evaluation methods, design systems and algorithms to improve agent performance, and collect and curate human and synthetic data to improve the capability and behavior of agent systems. This is hands-on work with immediate product impact at real-world scale.
You're excited about this opportunity because you will...

• Work directly with leadership and see your research deployed at real-world scale - small team, massive reach.
• Move fast without bureaucracy - rapid iteration, high autonomy, and no layers of politics.
• Have access to global data scale, robust compute, and a platform primed for AI transformation.
• Shape how AI transforms commerce, building intelligent and adaptive experiences for millions of Consumers, Merchants, and Dashers.

We're excited about you because you have...

• Experience with the latest AI tools building AI products
• Familiarity with building agent solutions, including context management, defining evals, measuring performance
• Strong knowledge of reinforcement learning techniques
• Experience building infra for large-scale reinforcement learning and multi-agent reinforcement learning
• Experience at frontier labs (OpenAI, Anthropic, DeepMind) or top AI startups.
• A builder mindset - you're energized by experimentation, move quickly, and stay close to the work
• Strong cross-functional instincts and a natural ability to bring research and product teams together.
• Nice to have: PhD with AI or other scientific domains

About the Team

The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering's evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers.
About the Role

We're hiring a Data Solutions Engineer with deep expertise in distributed databases, particularly Apache Cassandra, Redis, Kafka, and database agnostic abstractions. In this role, you will design, optimize, and scale distributed data access layers that power DoorDash's most critical systems, ensuring high availability, low latency, and fault tolerance.

You'll serve as a hands-on architect and technical partner to product engineering and infrastructure teams, helping translate complex business requirements into resilient and scalable data models. Your work will directly influence the evolution of Taulu, DoorDash's unified storage abstraction layer, by shaping best practices and identifying platform gaps through real world engagements.

This is a high-impact, cross functional role that combines deep technical expertise with a customer centric approach. You'll lead solutioning engagements from design through production, drive the adoption of Taulu modeling best practices, and ensure that our systems meet goals around reliability, cost efficiency, and velocity. You must be located in San Francisco, Sunnyvale, Seattle or New York for this hybrid opportunity.
You're excited about this opportunity because you will...

• Design and implement highly scalable, fault tolerant distributed database solutions using Taulu, Apache Cassandra, Redis, Kafka, and other paved path storage solutions.
• Architect and optimize multi-region, globally distributed systems to meet our high standards for availability, latency, and throughput.
• Lead data modeling, performance tuning, and capacity planning for large-scale, mission-critical storage workloads.
• Partner with product engineering and infrastructure teams to deeply understand domain specific data needs and guide them in adopting paved path storage solutions.
• Serve as the DRI for solutioning engagements, owning modeling in Taulu from experimentation through launch and scale.
• Shape the evolution of Taulu by identifying abstraction gaps and converting customer feedback into platform improvements.
• Apply workload-aware design patterns, including caching strategies, partitioning, and consistency tuning to improve performance and efficiency.
• Drive adoption of operational best practices across observability, schema design, capacity planning, and cost optimization across storage systems.
• Promote clarity and continuity by contributing to solutioning playbooks, decision logs, and architectural documentation.

We're excited about you because...

• You have 10+ years of experience designing and scaling distributed data systems, with deep expertise in NoSQL technologies like Apache Cassandra, DynamoDB, or ScyllaDB.
• You have a strong command of distributed system concepts such as replication, partitioning, tunable consistency, and failure recovery.
• You've led data modeling efforts for high-throughput, low-latency workloads and understand the real-world trade-offs involved in NoSQL schema design.
• You are experienced with caching technologies like Redis or Memcached and know how to layer them effectively over storage systems to optimize for performance and cost.
• You have a customer-first mindset, and thrive when working closely with product and platform teams to translate complex requirements into clean, scalable data models.
• You are skilled at communicating complex architecture decisions and building alignment across infrastructure and product engineering organizations.
• You have a track record of mentoring engineers, influencing data architecture at scale, and fostering best practices in reliability, observability, and data access patterns.
• You document decisions, share learnings, and take pride in contributing to reusable playbooks and durable frameworks for others to build upon.
• Bonus: You've worked on or contributed to open-source distributed databases.

Compensation

The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee's work location. Ranges are market-dependent and may be modified in the future.

In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.

DoorDash cares about you and your overall well-being. That's why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.

To learn more about our benefits, visit our careers page here.

See below for paid time off details:

• For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
• For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).

The national base pay range for this position within the United States, including Illinois and Colorado.

$203,500-$299,300 USD