Senior Associate, AI Solutions Architect, Marketing Technology
About this role
The Marketing Technology team at DoorDash builds tools, data systems, and processes that help teams acquire new customers, drive retention, and grow new business lines. Team members develop personalized and relevant content across owned and paid channels while partnering with Product, Engineering, Data Science, and Analytics groups.
Working alongside existing Marketing Technology AI Solutions Architects, the Senior Associate, AI Solutions Architect identifies marketing problems and prototypes, codes, and ships AI-powered tools such as automated reporting, QA frameworks, and workflow optimizations. Responsibilities include building MVPs, integrating AI solutions into the marketing stack, evaluating third-party platforms, and supporting the AI Center of Excellence.
Ideal candidates bring two to four years of experience at the intersection of marketing and technology with a hands-on builder mindset. Successful practitioners possess technical coding skills in languages like JavaScript, TypeScript, or Python, and demonstrate comfort working directly with engineering and product partners in ambiguous environments.
What you will do
- Build and deploy AI-powered tools and automations including automated reporting, quality assurance frameworks, and workflow optimizations.
- Develop minimum viable products and proof-of-concepts, then iterate based on user feedback within a defined workstream.
- Contribute to AI training materials, prompt and template libraries, and workshops to drive adoption across marketing teams.
- Partner with Data Engineering, Analytics, and Product teams to integrate AI solutions into the existing marketing technology stack.
- Evaluate third-party AI platforms and APIs to identify options that fit the marketing technology infrastructure.
- Track and report on the impact of built AI solutions, including efficiency gains and quality improvements.
- Help identify and automate time-consuming marketing processes across both AdTech and Marketing Platforms pods.
What you need
- Two to four years of experience at the intersection of marketing and technology with hands-on experience building tools or automations.
- Technical experience with JavaScript, TypeScript, or Python, including the ability to read, modify, and debug code.
- Familiarity with APIs, Postgres, ETLs, SQL, and data structures.
- Experience implementing AI solutions beyond basic chatbot usage, such as working with AI APIs, MCPs, prompt chains, and low-code or no-code platforms.
- Comfort working directly with Product or Engineering teams to develop solutions and collaborate on roadmaps.
- Strong communication skills with the ability to explain technical concepts clearly to non-technical partners.
- A builder and tinkerer mindset that is resourceful and comfortable with ambiguity.
Nice to have
- Experience with marketing technology platforms and tools
- Background in Marketing Ops, Marketing Analytics, or MarTech
Benefits
- 401(k) plan with employer matching
- 16 weeks of paid parental leave
- Wellness benefits
- Commuter benefits match
- Flexible paid time off/vacation plus 80 hours of paid sick time per year
- Medical, dental, and vision benefits
Skills and tech stack
Questions candidates ask
What is the compensation for this role?
The starting pay falls within a base salary range of $83,000 to $122,000 USD, which is localized according to the employee's work location. In addition to base salary, compensation for this role includes opportunities for equity grants.
What kind of background is required for this position?
Candidates need two to four years of experience at the intersection of marketing and technology, with hands-on experience building tools or automations. Technical proficiency in JavaScript, TypeScript, or Python and familiarity with AI APIs or low-code platforms are also required.
What will I actually be working on day-to-day?
You will spend your time prototyping, coding, and shipping AI-powered tools such as automated reporting, QA frameworks, and workflow optimizations. You will also develop MVPs, evaluate third-party AI platforms, and collaborate with Product, Engineering, and Analytics teams.