Sr. Manager, Software Development, Prime Video
Amazon · Seattle, Washington, USA ·
- Seniority
- Senior
- Category
- Management
Prime Video operates one of the largest and most complex streaming infrastructures in the world, serving hundreds of millions of customers across live sports, movies, and TV in more than 240 countries and territories. Ensuring that this infrastructure scales predictably, runs efficiently, and protects customer privacy is foundational to the business. We are hiring a Senior Software Development Manager to own three of the most consequential infrastructure disciplines within Prime Video.
This leader will report directly to the Director of READI and be accountable for how Prime Video plans for scale, drives cost and resource efficiency across core compute and AI infrastructure, and upholds customer privacy as a first-class engineering discipline. This is a broad role that spans predictive capacity planning, deep infrastructure optimization, and privacy engineering — requiring a leader who is equally comfortable in a data-driven forecasting review, an architecture deep-dive on compute and GPU efficiency, and a privacy risk assessment with legal and security partners.
The successful candidate is a seasoned engineering leader who builds and develops high-performing teams, sets multi-year technical strategy, and delivers measurable results in ambiguous, high-scale environments. They will lead through other managers and senior engineers, influence peer organizations and partner teams across Prime Video and AWS, and represent Prime Video’s infrastructure posture to senior leadership.
Key job responsibilities
PV Scale Forecasting & Capacity Assurance
Own the end-to-end discipline of forecasting demand and assuring capacity across Prime Video’s infrastructure footprint, ensuring the service scales reliably for both predictable growth and peak events (e.g., major live sports, tentpole launches, and global releases).
Own multi-year and event-based capacity models that translate business growth, content strategy, and traffic patterns into infrastructure demand across compute, storage, network, and CDN.
Lead capacity assurance for high-stakes live events, establishing headroom targets, load-testing regimes, and go/no-go readiness reviews with partner teams.
Build a forecasting practice grounded in data science and telemetry — improving forecast accuracy, quantifying confidence intervals, and reducing both over-provisioning waste and under-provisioning risk.
Partner on demand-planning and capacity-management processes with AWS, finance, and PV service teams so that capacity is secured ahead of need at the right cost.
Define the mechanisms (dashboards, reviews, and escalation paths) that give leadership confidence that Prime Video will scale for every moment that matters.
PV Infrastructure Efficiency (Core Compute & AI Infrastructure)
Drive infrastructure efficiency as a durable, measurable engineering discipline across Prime Video’s core compute fleet and its rapidly growing AI/ML infrastructure, materially improving unit economics while protecting reliability and performance.
Set the efficiency strategy and roadmap for core compute (CPU fleets, containerized services, memory/DRAM footprint) and AI infrastructure (GPU/accelerator fleets, training and inference platforms).
Drive down infrastructure cost-to-serve and improve utilization through right-sizing, fleet consolidation, hardware refresh strategy, and adoption of more efficient compute and runtimes.
Optimize the efficiency of AI/ML workloads — GPU utilization, training throughput, inference cost per request — partnering with science and platform teams to eliminate waste in one of PV’s fastest-growing spend areas.
Establish efficiency goals with clear metrics (utilization, cost per stream/request, DRAM and energy footprint) and instrument the fleet so gains are visible, attributable, and durable.
Lead zero-based capacity and efficiency reviews, and represent PV in senior compute-allocation and cost-optimization forums.
PV Privacy
Own privacy as a first-class engineering discipline for Prime Video infrastructure, ensuring that customer data is handled in accordance with Amazon’s privacy commitments and global regulatory obligations by design and by default.
Own the privacy engineering roadmap for PV infrastructure — data handling, minimization, retention, access controls, and auditability across the services and fleets in scope.
Embed privacy-by-design into capacity, compute, and AI infrastructure decisions, ensuring new systems and AI/ML workloads meet privacy requirements before launch.
Partner closely with Legal, Security, and central Privacy teams to translate regulatory requirements (e.g., GDPR and regional privacy laws) into concrete engineering controls and mechanisms.
Build the mechanisms that detect, prevent, and remediate privacy risks — tooling, reviews, and metrics that make privacy posture measurable and continuously improving.
Champion a culture of privacy ownership across the team, raising the bar on how PV builds and operates infrastructure that customers trust.
About the team
READI (Reliability, Efficiency, Availability, Defense & Integrity) is the Prime Video organization chartered to keep one of the world’s largest streaming services fast, efficient, resilient, and trustworthy. We sit at the intersection of infrastructure, operations, and customer trust — the team that ensures Prime Video scales for every tentpole launch and live event, spends every infrastructure dollar wisely, and protects customer data by design.
This role anchors three of READI’s most strategic charters — scale forecasting and capacity assurance, infrastructure efficiency across core compute and AI infrastructure, and privacy engineering. You will lead a team of managers and senior engineers, and partner daily with Prime Video service teams, AWS, Finance, Legal, Security, and central Privacy. The work is high-visibility and high-impact: our decisions show up in customer experience during the biggest moments of the year, in Prime Video’s cost structure, and in the trust customers place in how we handle their data.
We are a team that thinks long-term, dives deep on data, and holds a high bar. We invest in our people, promote from within, and give leaders room to set strategy and own outcomes end to end. If you are energized by hard technical problems at massive scale and by building teams that raise the bar, you will fit right in.
This leader will report directly to the Director of READI and be accountable for how Prime Video plans for scale, drives cost and resource efficiency across core compute and AI infrastructure, and upholds customer privacy as a first-class engineering discipline. This is a broad role that spans predictive capacity planning, deep infrastructure optimization, and privacy engineering — requiring a leader who is equally comfortable in a data-driven forecasting review, an architecture deep-dive on compute and GPU efficiency, and a privacy risk assessment with legal and security partners.
The successful candidate is a seasoned engineering leader who builds and develops high-performing teams, sets multi-year technical strategy, and delivers measurable results in ambiguous, high-scale environments. They will lead through other managers and senior engineers, influence peer organizations and partner teams across Prime Video and AWS, and represent Prime Video’s infrastructure posture to senior leadership.
Key job responsibilities
PV Scale Forecasting & Capacity Assurance
Own the end-to-end discipline of forecasting demand and assuring capacity across Prime Video’s infrastructure footprint, ensuring the service scales reliably for both predictable growth and peak events (e.g., major live sports, tentpole launches, and global releases).
Own multi-year and event-based capacity models that translate business growth, content strategy, and traffic patterns into infrastructure demand across compute, storage, network, and CDN.
Lead capacity assurance for high-stakes live events, establishing headroom targets, load-testing regimes, and go/no-go readiness reviews with partner teams.
Build a forecasting practice grounded in data science and telemetry — improving forecast accuracy, quantifying confidence intervals, and reducing both over-provisioning waste and under-provisioning risk.
Partner on demand-planning and capacity-management processes with AWS, finance, and PV service teams so that capacity is secured ahead of need at the right cost.
Define the mechanisms (dashboards, reviews, and escalation paths) that give leadership confidence that Prime Video will scale for every moment that matters.
PV Infrastructure Efficiency (Core Compute & AI Infrastructure)
Drive infrastructure efficiency as a durable, measurable engineering discipline across Prime Video’s core compute fleet and its rapidly growing AI/ML infrastructure, materially improving unit economics while protecting reliability and performance.
Set the efficiency strategy and roadmap for core compute (CPU fleets, containerized services, memory/DRAM footprint) and AI infrastructure (GPU/accelerator fleets, training and inference platforms).
Drive down infrastructure cost-to-serve and improve utilization through right-sizing, fleet consolidation, hardware refresh strategy, and adoption of more efficient compute and runtimes.
Optimize the efficiency of AI/ML workloads — GPU utilization, training throughput, inference cost per request — partnering with science and platform teams to eliminate waste in one of PV’s fastest-growing spend areas.
Establish efficiency goals with clear metrics (utilization, cost per stream/request, DRAM and energy footprint) and instrument the fleet so gains are visible, attributable, and durable.
Lead zero-based capacity and efficiency reviews, and represent PV in senior compute-allocation and cost-optimization forums.
PV Privacy
Own privacy as a first-class engineering discipline for Prime Video infrastructure, ensuring that customer data is handled in accordance with Amazon’s privacy commitments and global regulatory obligations by design and by default.
Own the privacy engineering roadmap for PV infrastructure — data handling, minimization, retention, access controls, and auditability across the services and fleets in scope.
Embed privacy-by-design into capacity, compute, and AI infrastructure decisions, ensuring new systems and AI/ML workloads meet privacy requirements before launch.
Partner closely with Legal, Security, and central Privacy teams to translate regulatory requirements (e.g., GDPR and regional privacy laws) into concrete engineering controls and mechanisms.
Build the mechanisms that detect, prevent, and remediate privacy risks — tooling, reviews, and metrics that make privacy posture measurable and continuously improving.
Champion a culture of privacy ownership across the team, raising the bar on how PV builds and operates infrastructure that customers trust.
About the team
READI (Reliability, Efficiency, Availability, Defense & Integrity) is the Prime Video organization chartered to keep one of the world’s largest streaming services fast, efficient, resilient, and trustworthy. We sit at the intersection of infrastructure, operations, and customer trust — the team that ensures Prime Video scales for every tentpole launch and live event, spends every infrastructure dollar wisely, and protects customer data by design.
This role anchors three of READI’s most strategic charters — scale forecasting and capacity assurance, infrastructure efficiency across core compute and AI infrastructure, and privacy engineering. You will lead a team of managers and senior engineers, and partner daily with Prime Video service teams, AWS, Finance, Legal, Security, and central Privacy. The work is high-visibility and high-impact: our decisions show up in customer experience during the biggest moments of the year, in Prime Video’s cost structure, and in the trust customers place in how we handle their data.
We are a team that thinks long-term, dives deep on data, and holds a high bar. We invest in our people, promote from within, and give leaders room to set strategy and own outcomes end to end. If you are energized by hard technical problems at massive scale and by building teams that raise the bar, you will fit right in.