Software Engineer, Data and AI Platform

DoorDash; San Francisco, Sunnyvale (CA, CA); On-site; USD 131,000 - 192,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks of paid parental leave

wellness benefits

commuter benefits match

paid time off and paid sick leave

Job summary

DoorDash, Inc. is seeking an engineer to own the full path from a question to an answer in a data platform. You will work on agentic analytics, semantic layers, and the AI-enabled data tooling that power dashboards and reporting for thousands of users across major markets.

You will contribute to a scalable data platform, implement cross-filter semantics, and ensure safe, efficient execution of queries under variable load, while collaborating with teams across DoorDash’s data platform ecosystem.

Qualifications

• BS/MS/PhD in Computer Science or equivalent.
• 3+ years of industry experience in software engineering.
• Strong backend fundamentals, especially in Go and Python, plus production-grade service ownership.
• Shipped an LLM-powered feature with retrieval and grounding; built or extended an eval system.
• Experience with data platforms: semantic layers, data discovery, caching, and multi-tenant data platforms.
• Familiarity with cloud environments (AWS) and Kubernetes in production.
• Experience with MCP, agent frameworks, or tool-calling architectures in production.
• Experience with traditional and modern analytics tools and data governance.

Responsibilities

• Ship agentic analytics features to thousands of users with accurate numbers as a product.
• Build data platform for authoring, dashboards, drill-down, cross-filter semantics, and content certification.
• Stream large result sets to the browser and render interdependent tiles.
• Develop AI-enabled services and workflows, including self-serve tooling for AI assistants.
• Own query and adaptive caching path across multiple query engines and safe execution under burst traffic.
• Build and operate data discovery and metadata platforms for finding datasets and metrics.

Skills

Go

Python

LLM

Agent frameworks

Tool-calling architectures

Retrieval & grounding

Education

BS/MS/PhD in Computer Science

Tools

Kubernetes

AWS

MCP

Job description

DoorDash is building the world's most reliable on-demand, logistics engine for delivery! We're looking for talented engineers to help us develop a 24x7, global infrastructure system that powers DoorDash's three-sided marketplace of consumers, merchants, and dashers.

About the Team

Data Platform’s Data User Experience Engineering builds the products every DoorDash employee uses to answer questions with data. That portfolio includes our AI first reporting and authoring surface, Conversational analytics with AI, Semantic and Knowledge layer along with MCP and skills layer plus the full stack infrastructure that lets users and agents reach all of it. Our users span analysts, engineers, operators, and executives across DoorDash, Wolt, and Deliveroo, on a warehouse and OLAP footprint that includes Snowflake, Spark and Clickhouse. The team is a mix of engineers who have built AI & Data platforms and products at scale.

About the Role

You will own the full path from a question to an answer an operator can put in a deck without checking it twice. The BI reporting surfaces are converging, and deciding what that convergence looks like while someone is authoring, building a report, writing a query, asking why a number moved, or asking for the chart they were about to build by hand.

• Ship agentic analytics features to thousands of users where a wrong number is a real business decision made badly, and accuracy is the product.
• Build a data platform for authoring, dashboard runtime, drill-down and cross-filter semantics, scheduling and alerting, content certification and permissions, and the embedding path that puts the same components in front of external users.
• Streaming large result sets to the browser, rendering dozens of interdependent tiles.
• Build the AI experience inside that platform: agent-assisted query authoring, generated charts and widgets held to the same governance as hand-built ones.
• Evolve the semantic layer metric and dimension modeling, definition governance, lineage and expose metadata in forms a model can actually reason over.
• Own the query and adaptive caching path: planning and federation across different query engines and invalidation correctness, and safe execution under agent traffic that bursts and fans out.
• Develop AI-enabled services and workflows, including self-serve tooling for creating, evaluating, and improving AI assistants.
• Build and operate data discovery and metadata platforms that help users find the right datasets, dashboards, and metrics quickly and confidently.

We're excited about you because you have…

• B.S., M.S., or PhD. in Computer Science or equivalent.
• 3+ years of industry experience in software engineering.
• Strong backend fundamentals, especially in Go, Python and the ability to own a service in production.
• Shipped an LLM-powered feature to real users, hands-on with retrieval and grounding and built or meaningfully extended an eval system.
• Built meaningful pieces of data platform products- semantic layers, data discovery, reporting applications, caching systems and data applications.
• Familiarity with a cloud-based environment such as AWS and with Kubernetes in production.
• Experience with MCP, agent frameworks, or tool-calling architectures in production.
• Experience with traditional and modern reporting or analytics tooling, data governance, controls and multi-tenant data platforms.
• Prompt and context optimization at scale - caching, token budgeting, cost/latency tuning.
• Full stack experience is a plus.

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. The national base pay range for this position within the United States, including Illinois and Colorado. $130,600 - $192,000 USD.

Benefits

• 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)
• medical, dental, and vision benefits
• 11 paid holidays
• disability and basic life insurance
• family-forming assistance
• mental health program

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

Paid Time Off Details

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).

About DoorDash

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're