Senior Program Manager, Alexa Sensitive Content Intelligence (ASCI)

Job description

As a Senior Program Manager in the Trust Sensitive Content team, you will shape how Alexa protects hundreds of millions of customers from harmful content using generative AI and responsible AI guardrails.About the RoleYou start with the customer and work backwards — every program decision is anchored in customer trust and experience.This role blends strategic leadership with program management excellence. You will define vision, lead cross-functional program delivery, and build high-performing teams in an environment where problems are ambiguous, stakes are high, and innovation moves at pace.This is not a role for someone who follows playbooks — it is a role for someone who writes them. Four things set the right candidate apart above all else:1. Demonstrated Program Management — you have led large, complex, cross-functional programs end-to-end and have the track record to prove it2. Invent & Simplify — you don't manage complexity, you reduce it. You build scalable solutions where ambiguity existed before3. Mechanisms — you build repeatable, self-sustaining operating systems that scale without requiring heroics4. Data & LLM Fluency — you understand how large language models work, where they fail, and how data quality decisions upstream shape model behavior and customer outcomes downstreamKey job responsibilities Strategic Program Leadership (Ambiguity & Scope)* Define and execute strategic roadmaps for responsible AI programs — working backwards from customer problems, safety requirements, and regulatory needs* Translate high-ambiguity programs across AI quality, data integrity, and content safety into actionable plans with clear success metrics* Negotiate priorities, secure resources, and influence stakeholders across engineering, legal, science, and policy to deliver program value* Bring data and LLM awareness to strategic decisions — connect generative AI model behavior, data pipelines, and evaluation frameworks to customer outcomes2. Program Execution & Operational Excellence (Execution & Problem Complexity)* Own end-to-end delivery of multiple cross-functional programs simultaneously — build release schedules, manage dependencies, and mitigate risks proactively* Define and monitor success metrics (quality rates, audit pass rates, customer satisfaction signals) and report progress in Leadership Reviews to executive stakeholders* Build mechanisms — establish SLAs, audit frameworks, and operating workflows that drive accountability and long-term operational excellence* Use metrics to challenge assumptions, surface insights, and make the case for course corrections; understand the data quality and LLM evaluation signals that indicate program health* Govern program health through regular risk assessments, blocker tracking, and re-prioritization to balance short-term deliverables with long-term innovation goals & establish high standards for program documentation, decision-making, and execution discipline across the team* Empower teams to solve problems autonomously, recognize contributions, and maintain sustainable workloads3. Cross-Functional Program Influence (Scope & Influence)* Partner with engineering, data science, and policy teams to align roadmaps and resolve trade-offs (speed vs. accuracy, scalability vs. compliance, data richness vs. latency)* Champion program outcomes in strategic forums (MBR/QBR, OP1/OP2), articulating technical and business impacts to leaders up to L10* Advocate for reusable, scalable solutions that avoid reinvention and accelerate time-to-value for safety and quality programs* Engage with science and engineering teams on LLM behavior, data pipeline quality, and model evaluation design — bridge the gap between technical execution and program delivery* Build trust and alignment without direct authority in a matrixed organization4. Communication & Stakeholder Management (Communication & Impact)* Write clear, data-driven documents (6-pagers, program narratives, WBR decks) that align teams and secure buy-in from senior leaders* Resolve contentious issues by harmonizing diverse viewpoints — engineering feasibility, policy compliance, customer experience — through data-driven discussions* Maintain transparency via dashboards, status reports, and cross-team syncs to ensure accountability and agilityA day in the lifeNo two days look the same — but every day centers on protecting customer trust at scale. You move between strategy and execution, connecting the dots across science, engineering, and policy to deliver responsible AI programs that work. * Develop and iterate on scalable solutions for emerging content safety challenges — from defining evaluation frameworks for new LLM capabilities to designing guardrail mechanisms that reduce manual intervention* Lead weekly program reviews with engineering and science leads to track delivery, surface risks, and unblock teams* Write and present program narratives for MBR/QBR and leadership reviews that connect program health to customer outcomes* Partner with Applied Science to translate model behavior insights into actionable program requirements — closing the loop between data quality, model performance, and customer experience* Triage and resolve cross-team blockers across engineering, policy, and science partners — making trade-off decisions that balance speed, accuracy, and compliance* Review program metrics dashboards and drive course corrections based on data signals — not waiting for problems to surface, but building the mechanisms that catch them earlyAbout the teamThe Trust Sensitive Content and Feedback Intelligence organization pioneers the protection of customer trust in Alexa and Devices by identifying and mitigating sensiti