Senior Manager, Applied Science, Amazon Business System Integrations

Are you energized by building technology that makes life easier for business customers? If you enjoy working at the center of enterprise commerce, connecting Amazon Business with the procurement, ERP, and finance systems that organizations run on ethn Amazon Business System (ABS) Integrations team is the place for you.

We build systems integrations capabilities that let business customers buy on Amazon Business directly from the systems they already use. This includes APIs, protocols, and partner connections that make procurement faster, more automated, and more reliable at global scale. Our teams design, launch, and operates these integrations with a wide range of partners, and each launch has to work securely and seamlessly across many different systems, regions, and customer needs.

We are seeking a Senior Manager Applied Science to build and lead the science organization in Amazon Business Systems Integrations. This is a foundational leadership role spanning the full integrations portfolio. This role will hire, grow, and lead a team of applied scientists who define how we measure and improve the performance of AI agents and human-AI teams. A core part of the role is defining the science agenda itself - identifying which problems are most worth solving and where the highest-leverage bets lie. Directions worth exploring might include Organizational Intelligence (turning institutional knowledge into agent-consumable skills) AI Agent Experience / AiAX (agent observability and autonomous remediation) and contextual behavioral security that adapts enforcement in real time for human and agent sessions and anything which the defines how we measure and improve agents and human-AI teams i.e benchmarks, task suites, and metrics (accuracy cost-per-task task completion productivity) that turn subjective "it works" judgments into rigorous reproducible measurement that gates what we ship. There are no established industry patterns in this field and the team will set the scientific direction, determine how AI agents and people perceive reason and act reliably within computing environments at enterprise scale.

This role requires building, leading and retaining a high calibre applied science team spanning the Agentic Integrations portfolio. This leader will set the bar for scientific talent, create the growth paths, and build the culture that makes Amazon Business a destination for the best agent and human-AI researchers.


Key job responsibilities
• Set the long-term scientific vision and team strategy: Define what best-in-class agent performance evaluation and learning look like across Agentic WorkSpaces - for computer-using agents and human-AI teams alike. Chart a multi-year research roadmap and build the team and plan to deliver it. Secure buy-in from VP-level leadership.
• Hire and grow scientific talent: Own recruiting calibration development and retention for the science team. Mentor scientists toward senior and principal scope and raise the scientific bar across the organization.
• Direct research on highly ambiguous novel problems: Guide the team through foundational challenges in agent perception reasoning evaluation reliability and human-AI collaboration - problems where neither the approach nor the success criteria are pre-defined.
• Drive cross-organizational alignment: Work across partner teams (AgentCore Bedrock model teams Identity Security the MCP ecosystem) and across the Applied AI Solutions product portfolio with product and engineering leadership to ensure scientific decisions compose into a coherent product.
• Deliver measurable business impact: Ensure your team's research translates to customer outcomes: higher task accuracy lower cost-per-action faster time-to-production measurable productivity for human-AI teams and the trust that lets enterprises scale agent workflows.
• Establish scientific rigor and operational excellence: Set the standard for experimentation evaluation and reproducibility and the mechanisms that keep the science organization productive and accountable.
• Advance the state of the art: Enable and champion contributions to the external technical community through publications patents and open-source work that position AWS as the leader in the science of secure agent-computer interaction and human-AI teamwork.
• Translate science into shipped product. Partner with engineering, product, and program leaders to move models evaluation and learning systems from prototype into a decade-old production service operating at massive scale without compromising the reliability that customers depend on.
• Represent science in leadership and to customers. Be the scientific voice in org-level planning and roadmap decisions across AAWS and engage directly with enterprise customers on how agent performance safety and human-AI productivity are measured and earned.

Basic qualifications

• Master's degree in Computer Science, Machine Learning, AI, Statistics, or equivalent
• Experience building large-scale machine learning and AI solutions at Internet scale
• Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Preferred qualifications

• 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
• 5+ years of hands-on work in big data, machine learning and predictive modeling experience
• 5+ years of people management experience
• PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
• Experience in practical work applying ML to solve complex problems for large scale applications
• Experience working with big data, machine learning and predictive modeling
• Experience in people management
• Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
• Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language
• Experience researching actual applications

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