Sr. Manager, Prototyping AI and Customer Engineering, AWS Prototyping and AI Customer Engineering (PACE)

📍 Job Overview

Job Title: Sr. Manager, Prototyping AI and Customer Engineering, AWS Prototyping and AI Customer Engineering (PACE)

Company: Amazon

Location: Arlington, Virginia, United States; New York, New York, United States; Chicago, Illinois, United States

Job Type: Full-Time

Category: Revenue Operations / Sales Operations / GTM Enablement (with a strong AI/ML focus)

Date Posted: September 10, 2026

Experience Level: 10+ years

Remote Status: On-site

🚀 Role Summary

• Lead and manage high-performing, cross-functional teams focused on rapid AI and cloud solution prototyping for enterprise customers.

• Drive the strategic direction and operational execution of customer engagements, ensuring high-quality delivery and direct business impact.

• Cultivate strong partnerships with field stakeholders, including Sales, Solutions Architecture (SA), and Customer Success Management (CSM) leadership.

• Foster a culture of technical excellence, continuous learning, and people development within the prototyping and customer engineering organization.

• Translate complex customer challenges into tangible, working prototypes and solutions, accelerating their journey to production on AWS.

📝 Enhancement Note: This role sits within Amazon's AWS Prototyping and AI Customer Engineering (PACE) organization, which is a critical GTM enablement function. While not a traditional Revenue Operations or Sales Operations role, it requires a deep understanding of sales cycles, customer engagement, capacity planning, and operational rigor to drive business outcomes. The focus on AI and prototyping positions it at the cutting edge of customer engineering for cloud services.

📈 Primary Responsibilities

• Lead, coach, and develop a team of approximately 10-12 prototyping architects and technical program managers, organized into industry-aligned PODs (Financial Services, Retail & CPG, Canada).

• Own the end-to-end delivery quality and velocity of customer engagements, including executive briefing centers (EBCs), guided builds, and AI Discovery Lifecycle (AI-DLC) workshops.

• Establish and maintain technical standards for prototypes, ensuring they meet production-grade quality and effectively address customer needs.

• Build and nurture strategic relationships with field leadership across Sales, SA, and CSM to understand pipeline, prioritize engagements, and secure prototyping capacity for critical accounts.

• Implement and manage robust operational mechanisms, including engagement intake, prioritization, capacity planning, allocation, and tracking of prototype-to-production outcomes.

• Maintain deep technical expertise in Generative AI (GenAI), agentic AI (AgentCore, Bedrock Agents), foundation model deployment (SageMaker, EKS), and multi-agent systems to guide technical decisions and sustain credibility.

• Collaborate with peer managers and leadership to balance capacity across verticals, share best practices and reusable assets, and maintain a unified quality bar for the PACE organization.

• Identify recurring patterns in customer engagements and codify them into reusable assets such as reference architectures, starter kits, and workshop frameworks to accelerate future delivery and support scaling efforts.

• Own hiring, onboarding, performance management, and career development for all team members, fostering an environment of growth and accountability.

📝 Enhancement Note: The responsibilities highlight a blend of people management, technical leadership, strategic stakeholder management, and operational execution, typical of a senior leadership role within a customer-facing, GTM-aligned technical organization. The emphasis on "prototype-to-production tracking" and "connecting delivery to business outcomes" underscores the revenue-generating impact of this role.

🎓 Skills & Qualifications

Education:

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Experience:

• Minimum of 7+ years of experience in managing technical, enterprise customer-facing resources, or equivalent experience in a leadership role driving complex technical projects.

• Proven track record of building and scaling prototyping, rapid delivery, or solutions architecture teams that operate at the intersection of sales engineering and product development.

• Experience managing geographically distributed teams across multiple time zones, including cross-border teams. Required Skills:

• Demonstrated ability to build strong relationships with senior technical and business stakeholders (VP/C-level) and translate their business problems into actionable technical solutions.

• Expertise in leading technical teams through ambiguous customer problems, with sound judgment on prototype development and delivery timelines.

• Deep understanding of software development tools and methodologies, with a focus on agile and rapid iteration.

• Proven experience working directly with enterprise customers on complex technical engagements, including architecture design, proof-of-concept (POC) development, and guiding production deployments.

• Strong people management skills, including coaching, mentoring, performance management, and career development.

• Excellent communication, presentation, and interpersonal skills, with the ability to context-switch between technical coaching and executive-level discussions. Preferred Skills:

• Hands-on experience with generative AI technologies, including foundation models, retrieval-augmented generation (RAG), agentic architectures, and multi-agent systems.

• Familiarity with AWS AI/ML services such as Amazon Bedrock, AgentCore, Amazon SageMaker, Amazon Q, and broader cloud-native architectures.

• Experience with cloud infrastructure, containerization (e.g., EKS), and modern application development paradigms.

• Direct experience within Financial Services (FSI), Retail, or Consumer Packaged Goods (CPG) industries is a strong plus.

• Knowledge of software development lifecycle (SDLC) and DevOps practices.

📝 Enhancement Note: The "7+ years of management of technical, enterprise customer facing resources" combined with the "10+ years" AI experience level suggests this role is for a seasoned leader. The preferred qualifications heavily lean into AI/ML and AWS services, indicating a strategic focus on these advanced technologies.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Candidates are expected to have a strong understanding of and experience with building and managing portfolios of technical projects, particularly in the context of customer engagements and GTM initiatives.

• Evidence of managing a pipeline of customer engagements, including intake, prioritization, and resource allocation strategies.

• Demonstrated ability to establish and enforce quality standards for technical deliverables, such as prototypes and reference architectures.

• Experience in developing and implementing operational mechanisms to track project progress, resource utilization, and business impact.

• Familiarity with systems that connect technical delivery efforts to tangible business outcomes and revenue generation. Process Documentation:

• Ability to define and document optimal workflows for rapid prototyping and customer engagement lifecycles.

• Experience in creating and maintaining documentation for reusable assets like reference architectures, starter kits, and workshop frameworks.

• Skills in developing processes for performance measurement, reporting, and continuous improvement of delivery mechanisms.

• Understanding of how to codify best practices and patterns from customer engagements into scalable and repeatable processes.

📝 Enhancement Note: While a formal "portfolio" in the traditional sense might not be required for application submission, the job description strongly implies that candidates will be evaluated on their experience and ability to manage and optimize a portfolio of technical engagements and internal processes. This is a critical aspect for operations-focused roles.

💵 Compensation & Benefits

Salary Range:

• Chicago, Illinois: $201,000 - $272,000 USD annually

• New York, New York: $221,100 - $299,200 USD annually

• Arlington, Virginia: $201,000 - $272,000 USD annually

Benefits:

• Comprehensive health insurance package including medical, dental, and vision coverage.

• Prescription drug insurance and basic life & AD&D insurance, with options for supplemental life plans.

• Employee Assistance Program (EAP) and Mental Health Support services.

• Medical Advice Line for health consultations.

• Flexible Spending Accounts (FSAs) for healthcare and dependent care.

• Adoption and Surrogacy Reimbursement coverage.

• 401(k) retirement savings plan with employer matching.

• Generous Paid Time Off (PTO) and parental leave policies.

• Restricted Stock Units (RSUs) as part of the overall compensation package. Working Hours:

• Standard full-time position, typically 40 hours per week. While core hours are expected, the role may require flexibility to meet customer needs and project deadlines, especially given the global nature of AWS.

📝 Enhancement Note: The salary ranges provided are specific to the listed US locations. The "AI_salary_minvalue" and "AI_salary_maxvalue" from the input data were used to establish these ranges, with the highest range for New York reflecting its higher cost of living and market demand. The benefits list is comprehensive and directly extracted from the provided data, with RSUs being a key component of Amazon's total compensation.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology / Cloud Computing / Artificial Intelligence

Company Size: Large Enterprise (Amazon is a global conglomerate with over 1.5 million employees worldwide)

Founded: 1994 (Amazon's long history signifies stability and continuous innovation)

Team Structure:

• The PACE team is described as a "small, high-output team" operating at the frontier of customer solutions on AWS.

• It consists of integrated PODs, each typically including prototyping architects and a technical program manager, aligned to specific industry verticals (FSI, Retail & CPG, Canada).

• The Sr. Manager will lead a team of approximately 10-12 individuals, managing both individual contributors and potentially other leads or senior architects.

• The structure emphasizes cross-functional collaboration between delivery teams, field stakeholders (Sales, SA, CSM), and potentially product teams. Methodology:

• Data-Driven Decision Making: The role requires driving operational mechanisms and reporting that connects delivery to business outcomes, implying a strong reliance on data for prioritization and performance assessment.

• Agile & Rapid Iteration: The core function involves building working prototypes and delivering guided builds that "compress months of development into days," highlighting an agile and rapid delivery methodology.

• Customer-Centric Problem Solving: The team works on "complex AI and cloud challenges," focusing on moving "from idea to production," emphasizing a customer-centric approach to solution development.

• Continuous Improvement: Identifying patterns and codifying them into reusable assets suggests a commitment to learning from engagements and improving future delivery efficiency.

Company Website: https://www.amazon.com

📝 Enhancement Note: Amazon's culture is known for its customer obsession, bias for action, and high ownership. Within AWS PACE, this translates to a fast-paced, results-oriented environment focused on cutting-edge technology and direct customer impact. The "small, high-output team" description suggests a lean, agile structure where individual contributions are highly visible and impactful.

📈 Career & Growth Analysis

Operations Career Level: Sr. Manager, leading a critical customer-facing technical delivery team within AWS. This role represents a significant leadership opportunity, managing direct reports and influencing GTM strategy for key industry verticals.

Reporting Structure: The Sr. Manager will report to the PACE North America Leader, indicating a clear hierarchy within the AWS PACE organization. They will also collaborate closely with peer managers and field leaders.

Operations Impact: This role has a direct impact on revenue generation by accelerating customer commitments through working prototypes and expert guidance. The quality and velocity of engagements directly influence customer adoption of AWS services and AI solutions, displacing competitors and driving adoption.

Growth Opportunities:

• Leadership Expansion: Potential to grow into larger leadership roles within PACE or other AWS customer-facing organizations, managing broader teams or multiple industry verticals.

• Strategic Influence: Opportunity to shape the strategy and operational models for AI and cloud prototyping across North America.

• Technical Specialization: Deepen expertise in cutting-edge AI technologies (GenAI, agentic systems) and cloud architecture, becoming a recognized authority.

• Cross-Functional Mobility: Potential to move into related roles within AWS, such as Solutions Architecture leadership, Professional Services, or even product management focused on AI/ML services.

• Mentorship & Development: Significant opportunity to mentor and develop a team of talented technical professionals, fostering their career growth.

📝 Enhancement Note: The role is positioned as a senior leadership opportunity with substantial impact. Growth paths are clearly linked to expanding leadership scope, strategic influence, and deepening technical expertise within the rapidly evolving AI and cloud domains.

🌐 Work Environment

Office Type: On-site, requiring presence in one of the specified major metropolitan areas (Arlington, VA; New York, NY; or Chicago, IL). This indicates a preference for in-person collaboration, team building, and client interaction.

Office Location(s):

• Arlington, Virginia (likely near AWS offices in the DC metro area)

• New York, New York (major hub for Financial Services and technology)

• Chicago, Illinois (significant hub for Retail, CPG, and Financial Services) Workspace Context:

• Collaborative Environment: The role necessitates building and maintaining deep stakeholder relationships, implying a highly collaborative workspace where interaction with Sales, SA, and CSM teams is frequent.

• Technology-Rich: As part of AWS, the team will have access to state-of-the-art cloud services, AI/ML tools, and development environments.

• Dynamic Pace: PACE operates at the "frontier of what customers are building," suggesting a fast-paced, dynamic environment where innovation and rapid problem-solving are key.

• Industry Focus: Teams are aligned to industry verticals, fostering specialized knowledge sharing and collaboration within those domains.

Work Schedule:

• Standard 40-hour work week is the baseline, but the nature of customer engagements and leadership responsibilities may require flexibility to meet deadlines and support critical client needs across different time zones.

📝 Enhancement Note: The on-site requirement points to a traditional office-based work environment with opportunities for direct team interaction and client-facing activities. The specific locations are strategic hubs for the industries served by this role.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Likely a recruiter screen to assess basic qualifications, experience, and alignment with the role.

• Hiring Manager Interview: Focus on leadership experience, team management, operational capabilities, and strategic thinking. Expect questions related to managing technical teams, driving results, and stakeholder management.

• Technical Deep Dive: Interviews with peer managers or senior architects to assess technical acumen, particularly in AI/ML, cloud architecture, and prototyping methodologies.

• Stakeholder Interviews: Conversations with field leaders (Sales, SA, CSM) to evaluate partnership-building skills, understanding of GTM dynamics, and ability to influence.

• Leadership Principles Interview: Amazon's leadership principles are heavily emphasized. Expect behavioral questions designed to assess your alignment with these principles (e.g., Customer Obsession, Ownership, Bias for Action, Dive Deep, Invent and Simplify).

• Final Interview: Potentially with a higher-level leader to confirm overall fit and strategic alignment.

Portfolio Review Tips:

• Focus on Impact: When discussing past projects or engagements, emphasize the business impact and revenue influence achieved, not just technical execution. Quantify results wherever possible (e.g., "accelerated customer commitment by X%", "influenced $Y in new revenue").

• Showcase Leadership: Highlight examples of how you have led, coached, and developed technical teams to achieve challenging goals.

• Demonstrate Operational Rigor: Be prepared to discuss your experience with capacity planning, engagement prioritization, process improvement, and establishing quality standards.

• Illustrate Stakeholder Management: Provide specific examples of how you have built and maintained relationships with senior sales and technical leaders, and how you have partnered effectively to drive customer success.

• Highlight AI/ML Expertise: Showcase your understanding and experience with AI technologies, cloud architectures, and rapid prototyping methodologies. Be ready to discuss specific projects or initiatives.

Challenge Preparation:

• Leadership Principles Scenarios: Prepare STAR method (Situation, Task, Action, Result) responses for common Amazon Leadership Principles, especially those relevant to management, customer engagement, and technical delivery.

• Operational Scenarios: Be ready to discuss how you would handle common operational challenges, such as capacity constraints, prioritization conflicts, or quality issues.

• Technical Scenarios: Prepare to discuss high-level technical challenges related to AI/ML prototyping and cloud architecture, demonstrating your ability to guide technical teams.

• Strategic Thinking: Be prepared to articulate your approach to building and managing a high-performing team, driving business outcomes, and fostering innovation.

📝 Enhancement Note: The interview process for a role like this at Amazon is rigorous and heavily focused on leadership principles and demonstrated impact. Candidates should prepare extensively for behavioral questions and be ready to articulate their experience with specific, quantifiable examples.

🛠 Tools & Technology Stack

Primary Tools:

• AWS Cloud Services: Deep familiarity with the AWS ecosystem is paramount. Specific services mentioned include:

  • Amazon Bedrock: For accessing foundation models.
  • AgentCore / Bedrock Agents: For building agentic AI applications.
  • Amazon SageMaker: For building, training, and deploying machine learning models.
  • Amazon Elastic Kubernetes Service (EKS): For container orchestration.
  • Amazon Q: For generative AI-powered assistant capabilities.

• Prototyping & Development Tools: Proficiency with development environments, version control systems (e.g., Git), and potentially CI/CD tools for rapid iteration.

• Project Management Tools: Experience with tools for managing tasks, timelines, and resources (e.g., Jira, Asana, or internal AWS equivalents).

Analytics & Reporting:

• AWS Analytics Services: Familiarity with AWS data analytics services (e.g., QuickSight for dashboards, S3 for data lakes) will be beneficial for tracking engagement success and operational metrics.

• Business Intelligence (BI) Tools: Ability to interpret and present data using BI tools to stakeholders.

• Internal AWS Reporting Mechanisms: Expect to utilize and contribute to internal AWS reporting systems for pipeline, capacity, and business outcomes.

CRM & Automation:

• CRM Systems: While not explicitly mentioned, familiarity with CRM systems (like Salesforce) used by sales teams for pipeline management is advantageous for stakeholder collaboration.

• Automation Tools: Understanding of automation principles for development workflows and potentially customer-facing demos.

📝 Enhancement Note: The technology stack is heavily centered around AWS, with a specific emphasis on AI/ML services. Candidates must demonstrate hands-on experience or a strong understanding of how to leverage these services for rapid prototyping and customer solutions.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: A core Amazon principle, meaning understanding and prioritizing customer needs above all else. For this role, it translates to deeply understanding customer challenges and delivering solutions that provide tangible value.

• Ownership: Taking full responsibility for engagements, team performance, and business outcomes. This means proactively identifying issues and driving solutions.

• Bias for Action: Moving quickly and decisively, especially in customer engagements and prototype development, without sacrificing quality.

• Invent and Simplify: Continuously seeking innovative ways to solve customer problems and simplifying complex technical challenges into manageable solutions.

• Dive Deep: Understanding the technical nuances of AI/ML and cloud architectures to effectively guide teams and provide expert advice.

• Earn Trust: Building credibility with both the team and external stakeholders through technical expertise, reliability, and transparent communication.

Collaboration Style:

• Cross-Functional Integration: Seamless collaboration with Sales, Solutions Architecture, and Customer Success Management teams is critical. The role acts as a bridge between field demand and delivery execution.

• Team Empowerment: Fostering an environment where team members feel empowered to innovate, take ownership, and contribute to decision-making.

• Knowledge Sharing: Actively promoting the sharing of best practices, reusable assets, and lessons learned across PODs and the wider PACE organization.

• Feedback Culture: Encouraging open feedback loops within the team and with stakeholders to drive continuous improvement.

📝 Enhancement Note: Amazon's leadership principles heavily influence the team culture. Candidates should demonstrate how their values and working style align with these principles, particularly in a fast-paced, customer-focused, and technically advanced environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving AI Landscape: Keeping pace with the constant advancements in Generative AI, foundation models, and agentic architectures requires continuous learning and adaptation.

• Balancing Speed and Quality: The mandate for rapid prototyping ("in days") while maintaining "production-grade" quality requires significant operational discipline and technical expertise.

• Managing Diverse Stakeholder Needs: Aligning the priorities and expectations of multiple field teams (Sales, SA, CSM) and various industry verticals can be complex.

• Team Development and Retention: Attracting and retaining top AI and cloud talent in a competitive market, while coaching a mix of experience levels.

• Bridging the Gap: Effectively translating complex customer business problems into technically feasible and impactful AI prototypes.

Learning & Development Opportunities:

• Cutting-Edge Technology Exposure: Direct involvement with the latest AWS AI/ML services and cutting-edge AI research and development.

• Leadership Skill Enhancement: Opportunities to refine management, strategic planning, and operational leadership skills within a renowned tech organization.

• Industry Specialization: Deepening expertise in key verticals like Financial Services, Retail, and CPG, understanding their unique AI/ML adoption challenges.

• Cross-Functional Learning: Gaining insights into sales strategies, customer success methodologies, and broader AWS product roadmaps.

• Formal Training & Certifications: Access to AWS training resources and potential for certifications in AI/ML and cloud technologies.

📝 Enhancement Note: The challenges presented are inherent to leading innovation in a high-growth, technically complex field. The growth opportunities are significant, offering a path for individuals passionate about AI and leadership to make a substantial impact.

💡 Interview Preparation

Strategy Questions:

• Team Leadership & Management: "Describe a time you had to lead a team through a technically challenging or ambiguous project. How did you ensure quality and timely delivery?" "How do you coach and develop technical talent, particularly in rapidly evolving fields like AI?" "How do you manage performance for individuals with different skill sets and career aspirations?"

• Operational Excellence: "How do you approach capacity planning for a customer-facing technical delivery team?" "Describe your process for prioritizing incoming customer engagements when resources are constrained." "How have you implemented mechanisms to track the business impact of technical delivery efforts?"

• Stakeholder Management: "How do you build and maintain effective relationships with sales and solutions architecture leaders?" "Describe a situation where you had to influence senior stakeholders to adopt a particular strategy or resource allocation." "How do you handle conflicting priorities from different field teams?"

Company & Culture Questions:

• "Why are you interested in Amazon and the AWS PACE organization specifically?"

• "How do your personal values align with Amazon's Leadership Principles?"

• "Describe your experience working in a fast-paced, high-output environment. How do you maintain focus and drive results?"

• "How do you foster a culture of innovation and continuous improvement within your team?" Portfolio Presentation Strategy:

• Quantify Impact: For any project or initiative you discuss, be ready to present concrete metrics demonstrating success (e.g., revenue influenced, adoption accelerated, efficiency gains).

• STAR Method: Structure your answers using the STAR method (Situation, Task, Action, Result) for behavioral and situational questions.

• Case Study Focus: Prepare 2-3 detailed examples of complex customer engagements where you or your team built impactful prototypes or solutions. Focus on the problem, your team's approach, the technical solution, and the business outcome.

• Operational Process Examples: Be ready to walk through how you've designed or improved processes for engagement intake, capacity planning, or quality assurance.

• Technical Depth: Be prepared to discuss the AI/ML and cloud architecture aspects of your projects, demonstrating your technical understanding and ability to guide technical teams.

📝 Enhancement Note: Amazon interviews are known for their rigor, especially around Leadership Principles. Candidates should prepare specific examples using the STAR method and be ready to articulate their strategic and operational thinking.

📌 Application Steps

To apply for this operations position:

• Submit your application through the Amazon Jobs portal via the provided URL.

• Resume Optimization: Tailor your resume to highlight experience in technical team leadership, AI/ML, cloud architecture, customer-facing engagements, operational management, and stakeholder relationship building. Use keywords from the job description.

• Portfolio Preparation: While not explicitly requested as a submission document, prepare detailed case studies and examples of your work in leading technical teams, managing customer engagements, and driving operational improvements. Be ready to discuss these in detail during interviews.

• Leadership Principles Alignment: Research and understand Amazon's Leadership Principles. Prepare specific examples from your career that demonstrate your alignment with these principles, particularly Customer Obsession, Ownership, Bias for Action, and Dive Deep.

• Company & Role Research: Thoroughly research AWS PACE, its mission, the industries it serves (FSI, Retail, CPG), and the current AI/ML landscape. Understand how this role contributes to Amazon's broader business objectives.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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