Associate Manager, QA Strategy

About the TeamThe Performance Excellence (PE) team is redefining how DoorDash measures, governs, and improves quality at scale. We are building an AI-first, automated QA ecosystem that delivers high-precision insight across 100% of customer interactions—powering performance management, coaching, risk detection, and product feedback in near real time.After successfully scaling Automated QA (AQA) across Tier 1 Support, we are expanding into high-impact, higher-risk domains including Fraud, Integrity, Trust & Safety, and in-house support. This work requires strong ownership of AI signal accuracy, refinement rigor, and end-to-end process design to ensure automation is trusted, fair, and operationally actionable.About the RoleAs Associate Manager, QA Strategy & Operations, you will own large-scale, AI-led quality programs from design through production. This is a senior IC / early people-manager role focused on building and governing automated QA systems, not running traditional QA operations. You will lead cross-functional initiatives that improve the accuracy, stability, and adoption of AI-generated quality signals, partnering closely with Product, ML, Engineering, Operations, and Policy teams. Your work will directly influence how DoorDash defines quality, manages performance, and mitigates risk at scale.You’ll report to the Senior Manager, QA Strategy & Operations within Performance Excellence (CXI).You’re excited about this role because you will…Own AI-led QA system expansion into complex domains (Customer Support, Fraud, Integrity, Risk, In-House), defining what is automatable vs. human-judgment required. Design and operationalize quality signals at scale, including rubric logic, precision thresholds, false-positive controls, and rollout gatesDrive signal accuracy and trust, partnering with ML and Calibration teams to improve precision, reduce FP/FN rates, and close dispute feedback loopsTranslate ambiguous quality problems into structured systems, from intake → signal design → calibration → launch → governanceInfluence the QA tech and model roadmap, prioritizing investments in automation, tooling, and infrastructure that improve signal reliabilityEstablish durable process frameworks (intake, SLAs, readiness criteria, documentation) that allow AI quality programs to scale safely and repeatablyLead cross-functional execution across Product, Engineering, Ops, and Policy without formal authority—driving clarity, alignment, and deliveryWe’re excited about you because…You have 6–8+ years of experience in strategy, program management, operations, product ops, or quality systems—ideally in AI-enabled or data-driven environmentsYou’ve worked on large-scale process or platform launches, where accuracy, governance, and change management mattered as much as speed.You are comfortable operating at the intersection of AI models, business rules, and operational workflowsYou have a strong intuition for signal quality—understanding false positives, calibration tradeoffs, thresholds, and downstream impactYou bring structured thinking and execution rigor, especially in ambiguous problem spaces with multiple stakeholdersYou can partner effectively with ML and Engineering teams, even if you are not a model builder yourselfHands-on experience with LLMs, prompt design, conversational analytics, or AI QA systems is a strong plusYou care deeply about building systems that are accurate, fair, trusted, and scalableNotice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC OnlyWe use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: CoveyCompensationActual compensation within the pay range listed below will be decided based on factors including, but not limited to, skills, prior relevant experience, and specific work location. Base salary is localized according to employee work location.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 for all regular employees, that includes paid time off, paid parental leave, wellness benefit and several paid holidays.Additionally, for full-time employees, DoorDash offers medical, dental, and vision benefits, disability and basic life insurance, an RRSP including an employer match, and a mental health program, among others.To learn more about our benefits, visit our careers page here.The base pay for this position ranges from our lowest geographical market up to our highest geographical market within British Columbia.$80,500—$115,000 CADAbout DoorDashDoorDash is committed to empowering local economies. We are a technology and logistics company that started with door-to-door delivery, and we seek team members who can help us expand to become the go-to for goods beyond food.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 offer comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.Our Commitment to Diversity and InclusionWe’re committed to growing and empowering a more inclusive community within our company, industry, and cities. We hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.If you need any accommodations, please inform your recruiting contact upon initial connection. #J-18808-Ljbffr