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

📍 Job Overview

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

Company: Amazon

Location: New York, New York, United States; Austin, Texas, United States; Seattle, Washington, United States

Job Type: Full-Time

Category: Revenue Operations / Sales Operations / GTM Strategy (Partner Ecosystem Focus)

Date Posted: May 13, 2026

Experience Level: Mid-Senior Level (5-10 years)

Remote Status: On-site (Requires ~25% Domestic Travel)

🚀 Role Summary

• Drive the strategic growth and operational scaling of AWS's partner-led AI prototyping program, focusing on Generative AI and Agentic AI solutions.

• Develop and implement robust enablement programs and reusable assets to empower technology partners in delivering high-quality AI prototypes independently.

• Define, track, and analyze key performance indicators (KPIs) to measure program success, drive continuous improvement, and demonstrate business impact.

• Collaborate closely with AWS Sales, Solutions Architects, and a diverse ecosystem of technology partners to expand AI adoption and accelerate customer success.

• Act as a force multiplier by translating successful AI prototyping patterns into scalable, repeatable mechanisms that drive non-linear impact across the industry.

📝 Enhancement Note: While the title is "Technical Program Manager," the responsibilities heavily lean into Revenue Operations and Go-To-Market (GTM) strategy, specifically within a partner ecosystem. The role involves program design, partner enablement, process scaling, and KPI management, all critical components of operationalizing a GTM strategy. The focus on "partner-led engagement" and "scalability" directly aligns with revenue operations' goal of driving predictable revenue through efficient channels. Therefore, this role is categorized as having strong Revenue Operations and GTM Strategy elements, with a significant Sales Operations component in managing partner relationships and opportunity routing.

📈 Primary Responsibilities

• Own and scale the partner-led AI prototyping program, defining strategy, qualification criteria, and growth targets that expand PACE's reach beyond the core team.

• Recruit, enable, and manage a growing ecosystem of technology partners through the "Amazon Designed, Partner Delivered" model, overseeing their journey from onboarding through production launch.

• Design and operate scalable enablement mechanisms, including partner summits, certification programs, and feedback loops, to ensure partners consistently deliver high-quality AI outcomes independently.

• Create and maintain reusable assets, industry reference architectures, and blueprints that enable partners and field teams to deploy AI solutions without direct PACE involvement.

• Establish and meticulously track program KPIs such as partner launch rates, production conversion, time-to-delivery, and overall business impact, leveraging data to continuously refine and improve program effectiveness.

• Partner effectively with Sales, Solutions Architecture, and field teams to accurately route and qualify AI opportunities across both direct and partner-led channels, ensuring alignment with business objectives.

• Whiteboard architecture patterns and contribute to shipping production-ready code or solutions, demonstrating technical acumen alongside program management skills.

• Experiment constantly and measure success by what actually makes it to production, embodying the fast-paced, results-oriented culture of the PACE team.

📝 Enhancement Note: The core responsibilities highlight a strong emphasis on program scaling, partner enablement, and data-driven performance management, which are pivotal in Revenue Operations. The "Amazon Designed, Partner Delivered" model implies a structured GTM approach for partners, requiring robust operational processes for onboarding, training, and performance tracking. The creation of reusable assets and reference architectures speaks to building scalable operational playbooks for partners.

🎓 Skills & Qualifications

Education: Bachelor's degree in Engineering, Computer Science, or a related technical field.

Experience:

• Minimum of 6+ years in project management disciplines, encompassing scope, schedule, budget, quality, risk, and critical path management.

Required Skills:

• Technical Program Management: Proven ability to manage complex technical projects from conception to delivery, with a strong understanding of project lifecycles.

• Partner Ecosystem Management: Experience in recruiting, enabling, and managing technology partners, fostering collaborative relationships and driving joint success.

• AI & ML Fundamentals: Solid understanding of Generative AI, Agentic AI, Large Language Models (LLMs), and RAG architectures to effectively guide partner development.

• Process Design & Optimization: Ability to design, implement, and refine scalable programs and processes that ensure quality and efficiency.

• Data Analysis & KPI Management: Proficiency in defining, tracking, and reporting on Key Performance Indicators (KPIs) and Service Level Agreements (SLAs) to drive business outcomes.

• Cross-functional Collaboration: Demonstrated success in working effectively with diverse teams, including Sales, Solutions Architecture, and engineering.

• Strategic Thinking: Capacity to develop long-term program strategies, identify growth opportunities, and translate business needs into actionable plans.

• Communication & Presentation: Excellent verbal and written communication skills, with the ability to present complex technical and program information to senior leadership and external stakeholders.

Preferred Skills:

• 5+ years of experience specifically in defining KPIs/SLAs used to drive multi-million dollar businesses and reporting to senior leadership.

• Experience managing projects across cross-functional teams, building sustainable processes, and coordinating release schedules.

• Familiarity with cloud computing concepts, particularly within the AWS ecosystem.

• Experience in designing and delivering partner enablement programs or certification curricula.

• Background in creating industry reference architectures or technical blueprints.

• Experience with AI-driven development tools and autonomous agent frameworks.

📝 Enhancement Note: The distinction between basic and preferred qualifications, particularly the emphasis on KPI definition for significant business impact and cross-functional project management with process building, strongly aligns with the requirements of a senior-level operations professional focused on scaling GTM initiatives. The inclusion of AI/ML fundamentals and cloud ecosystem knowledge is critical for this specialized role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Program Scaling Case Studies: Demonstrations of successfully scaling a program or initiative, ideally involving external partners or cross-functional teams, with clear metrics on growth and impact.

• Process Optimization Examples: Documented instances of designing or improving operational workflows, partner enablement processes, or project delivery mechanisms, highlighting efficiency gains.

• System Implementation Standards: Evidence of contributing to or leading the implementation of systems or frameworks that standardize partner delivery or operational reporting.

• ROI Demonstration: Case studies showcasing how initiatives led to measurable business impact, such as increased partner-led revenue, reduced time-to-market for AI solutions, or improved customer satisfaction.

Process Documentation:

• Workflow Design & Optimization: Examples of documented workflows for partner onboarding, enablement, support, and performance tracking, clearly illustrating the steps and decision points.

• Implementation & Automation: Evidence of implementing processes that leverage automation or repeatable patterns to achieve scale and consistency in partner engagement.

• Measurement & Performance Analysis: Examples of how performance metrics were defined, tracked, and analyzed to identify bottlenecks, inform strategic decisions, and demonstrate program value.

📝 Enhancement Note: For a role focused on scaling a partner program and operationalizing AI solutions, a portfolio demonstrating the ability to build and scale processes, manage complex engagements, and measure business impact is crucial. This section outlines the types of evidence that would showcase the candidate's operational and strategic capabilities.

💵 Compensation & Benefits

Salary Range:

• New York, NY: $163,600 - $221,300 USD annually

• Austin, TX: $148,700 - $201,200 USD annually

• Seattle, WA: $148,700 - $201,200 USD annually

Benefits:

• Comprehensive Health Insurance: Includes medical, dental, vision, and prescription coverage.

• Basic Life & AD&D Insurance: With options for supplemental life plans.

• Employee Assistance Program (EAP) & Mental Health Support: Resources for well-being.

• Medical Advice Line: Access to medical guidance.

• Flexible Spending Accounts (FSAs): For healthcare and dependent care expenses.

• Adoption and Surrogacy Reimbursement: Support for family-building.

• 401(k) Matching Program: Retirement savings support.

• Paid Time Off (PTO): Including vacation, sick leave, and holidays.

• Parental Leave: Support for new parents.

• Sign-on Payments: Additional compensation upon joining.

• Restricted Stock Units (RSUs): Equity grants as part of the compensation package.

Working Hours: Standard 40 hours per week, with expectations for flexibility to meet program demands and collaboration needs across different time zones.

📝 Enhancement Note: Salary ranges are provided for the specified locations. The total compensation package includes base salary, sign-on bonuses, and RSUs, which is typical for senior roles at Amazon. The benefits listed are extensive and align with large technology companies, offering robust support for employees' health, financial well-being, and personal life. The working hours are standard, but the nature of program management, especially with a partner ecosystem and global technology, implies a need for flexibility.

🎯 Team & Company Context

🏢 Company Culture

Industry: Cloud Computing, Artificial Intelligence, E-commerce, Technology Services. Amazon Web Services (AWS) is a leader in cloud infrastructure and services, driving innovation across a vast array of industries. The PACE team operates at the cutting edge of AI, working with leading-edge technologies to solve complex customer problems.

Company Size: Amazon is a global enterprise with hundreds of thousands of employees worldwide. This scale offers vast opportunities for collaboration, learning, and career advancement.

Founded: Amazon was founded in 1994 by Jeff Bezos. AWS was launched in 2006, rapidly growing to become the dominant cloud platform. This history signifies a culture of relentless innovation, customer obsession, and long-term vision.

Team Structure:

• PACE Team: A small, high-impact group comprising Prototyping Architects, Design Technologists, and Technical Program Managers. This structure fosters agility, direct collaboration, and rapid decision-making.

• Reporting Structure: The Sr. Technical Program Manager will likely report to a senior leader within the PACE organization or a broader AWS AI/Customer Engineering leadership role, with direct influence over the partner program's direction.

• Cross-functional Collaboration: The role is inherently collaborative, requiring deep engagement with AWS Sales, Solutions Architects, partner management teams, and technology partners. This necessitates strong relationship-building and communication skills.

Methodology:

• Data Analysis & Insights: The team emphasizes a data-driven approach to understand program performance, identify trends, and make informed decisions for scaling and optimization.

• Workflow Planning & Optimization: Focus on designing and refining efficient, repeatable processes for partner enablement and AI solution delivery.

• Automation & Efficiency: A constant drive to automate repetitive tasks and build scalable mechanisms that allow the team and its partners to achieve more with less direct oversight.

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

📝 Enhancement Note: Understanding Amazon's culture of customer obsession, innovation, and data-driven decision-making is key. The PACE team's agile and high-impact nature, combined with a focus on partner scaling, requires an operations professional who can thrive in a fast-paced, forward-thinking environment. The collaborative structure means success is heavily dependent on building strong cross-functional relationships.

📈 Career & Growth Analysis

Operations Career Level: This Sr. Technical Program Manager role is positioned at a mid-to-senior level, demanding significant autonomy, strategic input, and the ability to manage large-scale programs. It's a critical role for operationalizing a key GTM strategy for AI technologies.

Reporting Structure: The role reports into a leadership position within the AWS Prototyping and AI Customer Engineering (PACE) team. The upward reporting relationship will involve presenting program status, strategic recommendations, and performance metrics to senior management, influencing the direction of AI adoption through partners.

Operations Impact: The operations impact is direct and significant: by scaling the partner-led AI prototyping program, this role directly influences AWS's ability to accelerate AI adoption across a broader customer base. Success translates into increased customer success, deeper cloud adoption, and ultimately, revenue growth for AWS through its partner ecosystem. This role is crucial for operationalizing the GTM strategy for cutting-edge AI technologies.

Growth Opportunities:

• Operations Skill Advancement: Deepen expertise in scaling GTM programs, partner ecosystem management, and operationalizing AI technologies within a leading cloud provider.

• Leadership Development: Potential to move into management roles within PACE or other AWS GTM/operations teams, leading larger initiatives or teams.

• Specialization: Become a recognized expert in AI/ML prototyping program management and partner scaling within the AWS ecosystem, opening doors to roles in strategy, product management, or senior program leadership.

• Cross-functional Mobility: Opportunities to transition into roles within AWS Sales, Solutions Architecture, or partner management, leveraging a deep understanding of the partner ecosystem and technical solutions.

📝 Enhancement Note: This role offers a clear path for growth within a rapidly evolving field like AI and a dominant cloud platform. The emphasis on scaling, partner enablement, and strategic impact suggests opportunities for leadership development and specialization in high-demand areas of cloud and AI operations.

🌐 Work Environment

Office Type: The role is primarily on-site in Amazon's corporate offices located in Austin, Seattle, or New York. These offices are designed to foster collaboration, innovation, and productivity.

Office Location(s):

• Austin, Texas: Amazon has a significant presence in Austin, with modern office spaces designed to support a growing tech workforce.

• Seattle, Washington: Headquarters for Amazon, offering a dynamic work environment with extensive amenities and access to a vibrant tech community.

• New York, New York: Located in a major metropolitan hub, providing access to diverse talent and business opportunities.

Workspace Context:

• Collaborative Environment: Offices are equipped with meeting rooms, collaborative spaces, and open areas designed to encourage interaction and knowledge sharing among team members and cross-functional partners.

• Operations Tools & Technology: Access to Amazon's robust internal tools, cloud infrastructure (AWS), and collaboration platforms necessary for program management, data analysis, and communication.

• Team Interaction: Regular opportunities for in-person syncs, brainstorming sessions, and team-building activities with fellow PACE team members, sales teams, and partner representatives.

Work Schedule: While the core work hours are typically 40 hours per week, the dynamic nature of managing a partner program, especially with global technology partners and customer engagements, may require flexibility. This could involve occasional early morning or late afternoon calls to accommodate different time zones, or focused work periods to meet program milestones.

📝 Enhancement Note: The on-site requirement, coupled with significant travel, indicates a need for individuals who can effectively balance structured office work with external partner engagements and internal stakeholder meetings. The office environments are designed to support collaboration and productivity, which is essential for a role focused on scaling complex programs.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will review your application, focusing on alignment with basic qualifications and relevant experience.

• Hiring Manager Interview: A conversation with the hiring manager to assess your understanding of technical program management, partner ecosystem strategy, and AI technologies. Be prepared to discuss your experience with scaling programs and managing complex stakeholder relationships.

• Technical/Panel Interviews: Multiple rounds involving peers and senior team members. These interviews will likely include behavioral questions based on Amazon's Leadership Principles, technical deep-dives into AI/ML concepts, and scenario-based questions about program management, process design, and partner enablement. Expect discussions on how you'd approach scaling the partner program.

• Portfolio Presentation (Potential): You may be asked to present specific case studies from your portfolio that demonstrate your ability to design, scale, and measure the impact of operational programs, particularly those involving partners or complex technology deployments.

• Final Interview: A discussion with senior leadership to ensure cultural fit and strategic alignment.

Portfolio Review Tips:

• Quantify Impact: For each project, clearly articulate the problem, your solution, the operational processes you designed or optimized, and the quantifiable results (e.g., % increase in partner adoption, % reduction in time-to-delivery, $ revenue impact).

• Focus on Scalability: Highlight examples where you successfully scaled a program, process, or system, especially through partners or repeatable mechanisms. Emphasize the "how."

• Illustrate Process Design: Showcase your ability to document, design, and implement clear, efficient operational workflows. This could include partner onboarding flows, enablement tracks, or reporting structures.

• Demonstrate AI/Technical Acumen: Include projects that showcase your understanding of AI/ML concepts (LLMs, RAG, Agentic AI) and how you've translated technical capabilities into operational GTM strategies.

• Partner Ecosystem Experience: If possible, include case studies detailing your experience working with or managing technology partners, their enablement, and their role in driving business outcomes.

Challenge Preparation:

• Scenario-Based Questions: Prepare for questions like "How would you design an enablement program for 50 new AI partners?" or "What KPIs would you track for a partner-led prototyping initiative, and why?"

• Leadership Principles: Familiarize yourself with Amazon's 16 Leadership Principles and prepare specific STAR (Situation, Task, Action, Result) method examples for each, focusing on ownership, bias for action, deliver results, and dive deep.

• Technical Concepts: Refresh your understanding of Generative AI, LLMs, RAG, and agentic AI concepts, as well as typical cloud architecture patterns.

• GTM Strategy: Be ready to discuss how to operationalize a GTM strategy through a partner channel, focusing on scalability, enablement, and performance measurement.

📝 Enhancement Note: The interview process at Amazon is rigorous and heavily relies on behavioral questions tied to their Leadership Principles. For this role, demonstrating a track record of scaling operations, managing partners, and understanding AI technologies will be paramount. A well-curated portfolio is essential for showcasing practical experience.

🛠 Tools & Technology Stack

Primary Tools:

• Project Management Software: Proficiency in tools like Jira, Confluence, Asana, or similar for tracking project progress, managing tasks, and documenting workflows.

• Collaboration Platforms: Expertise with tools like Slack, Microsoft Teams, or Amazon Chime for day-to-day communication and team collaboration.

• Presentation Software: Advanced skills in PowerPoint, Google Slides, or similar for creating impactful presentations for stakeholders and partners.

Analytics & Reporting:

• Business Intelligence Tools: Experience with tools like Tableau, Power BI, Looker, or Amazon QuickSight for data visualization, dashboard creation, and performance reporting.

• CRM Systems: Familiarity with Salesforce or other CRM platforms for managing partner relationships, tracking opportunities, and understanding pipeline dynamics.

• Spreadsheet Software: Advanced proficiency in Microsoft Excel or Google Sheets for data manipulation, analysis, and reporting.

CRM & Automation:

• Cloud Platforms: Deep understanding of AWS services relevant to AI and machine learning (e.g., Amazon SageMaker, Bedrock, EC2, S3), and general cloud infrastructure.

• Automation Tools: Experience with workflow automation tools or scripting languages (e.g., Python) to streamline operational tasks and reporting.

• Data Warehousing/Databases: Familiarity with data warehousing concepts and SQL for querying and analyzing data from various sources.

📝 Enhancement Note: The role requires a strong command of project management and collaboration tools, alongside proficiency in data analysis and reporting platforms. A solid understanding of cloud technologies, particularly AWS, and experience with CRM systems are essential for managing partner relationships and tracking GTM performance.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: A fundamental principle at Amazon. For this role, it means deeply understanding partner needs and their customers' needs to drive successful AI adoption through the partner channel.

• Ownership: Taking full responsibility for the partner-led AI prototyping program, from strategy development to execution and performance.

• Bias for Action: Moving quickly to iterate on programs, enable partners, and deliver results, rather than getting stuck in analysis paralysis.

• Deliver Results: Focusing on measurable outcomes, specifically scaling the partner program and driving production deployments of AI prototypes.

• Dive Deep: Thoroughly understanding the technical aspects of AI, the partner ecosystem, and the operational challenges to find effective solutions.

• Invent and Simplify: Continuously seeking ways to improve processes, create reusable assets, and make it easier for partners to succeed.

Collaboration Style:

• Cross-functional Integration: Proactively engaging with Sales, Solutions Architects, and partner teams to ensure seamless alignment and support for the partner program.

• Process Review & Feedback: Fostering a culture of continuous improvement by actively seeking and incorporating feedback from partners, internal teams, and performance data.

• Knowledge Sharing: Openly sharing best practices, reference architectures, and lessons learned with partners and internal stakeholders to build a collective understanding and accelerate AI adoption.

📝 Enhancement Note: Amazon's culture is deeply ingrained in its Leadership Principles. For an operations role focused on scaling a partner program, embodying these principles – particularly customer obsession, ownership, bias for action, and delivering results – is critical for success and integration into the team.

⚡ Challenges & Growth Opportunities

Challenges:

• Scaling Partner Ecosystem: The primary challenge will be to effectively recruit, onboard, and enable a rapidly growing number of technology partners to deliver consistent, high-quality AI prototypes.

• Maintaining Quality at Scale: Ensuring that as the partner program expands, the quality and consistency of AI solutions delivered by partners remain high, meeting AWS's standards.

• Rapidly Evolving AI Landscape: Staying ahead of the curve in a fast-paced AI field, constantly adapting program strategies and enablement materials to incorporate new models, techniques, and tools.

• Balancing Strategic Vision with Tactical Execution: Developing a compelling long-term strategy for the partner program while simultaneously managing day-to-day operations, partner escalations, and enablement delivery.

Learning & Development Opportunities:

• AI/ML Specialization: Gaining deep expertise in emerging AI technologies and their application through cloud platforms and partner ecosystems.

• Program Management Mastery: Honing skills in designing, launching, and scaling complex, multi-stakeholder GTM programs within a world-class cloud organization.

• Partner Ecosystem Strategy: Developing a nuanced understanding of how to build and leverage technology partnerships for significant business impact.

• Industry Conferences & Certifications: Opportunities to attend relevant AI and cloud technology conferences, and potentially pursue certifications that enhance expertise.

• Mentorship: Access to experienced leaders within AWS who can provide guidance on career development, strategic thinking, and technical leadership.

📝 Enhancement Note: This role presents significant challenges in a cutting-edge field, which in turn offers substantial growth opportunities. Overcoming these challenges will require strong operational acumen, strategic thinking, and a proactive approach to learning and adaptation.

💡 Interview Preparation

Strategy Questions:

• "Describe your approach to designing and scaling a partner enablement program for a complex technology like Generative AI. What are the key components and how would you measure success?"

• "How would you operationalize an 'Amazon Designed, Partner Delivered' model for AI prototyping? What are the critical success factors and potential pitfalls?"

• "Given the rapid evolution of AI, how would you ensure your partner enablement materials and reference architectures remain current and relevant?"

Company & Culture Questions:

• "How do Amazon's Leadership Principles, such as 'Customer Obsession' and 'Bias for Action,' apply to your role in managing a partner program?"

• "Describe a time you had to influence stakeholders across different teams (e.g., Sales, Engineering, Partner Management) to achieve a program goal."

• "How do you approach building trust and long-term relationships with external partners?"

Portfolio Presentation Strategy:

• Storytelling with Data: Structure your case studies as compelling narratives, clearly outlining the challenge, your role, the operational solutions implemented, and the quantifiable business impact supported by data.

• Focus on Scalability Mechanisms: When presenting process improvements or program designs, emphasize the "how" behind their scalability. Did you use templates, automation, self-service portals, or standardized playbooks?

• Demonstrate Partner Engagement: If you have direct partner experience, highlight how you managed those relationships, supported their growth, and drove joint success.

• Prepare for Deep Dives: Be ready to answer detailed questions about your methodologies, the tools you used, the metrics you tracked, and the specific decisions you made. Anticipate questions about potential alternative approaches.

📝 Enhancement Note: Interview preparation should focus on demonstrating not only technical understanding but also strong operational, strategic, and people-management skills. Articulating how you embody Amazon's Leadership Principles and can translate technical capabilities into scalable GTM operations for partners will be key.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided Amazon Jobs link.

• Operations Portfolio Customization: Curate your resume and any supplementary materials to highlight experience in program scaling, partner enablement, process design, AI/ML technologies, and KPI management. Tailor your achievements to directly address the responsibilities outlined in this job description, emphasizing your GTM and Revenue Operations contributions.

• Resume Optimization: Ensure your resume clearly articulates your experience with project management disciplines, cross-functional collaboration, and driving business impact through operational initiatives. Use keywords relevant to AI, cloud, partner ecosystems, and program management.

• Interview Preparation: Thoroughly review Amazon's Leadership Principles and prepare STAR method examples that showcase your ownership, bias for action, ability to deliver results, and deep dives into complex problems, especially in an operational or partner context. Practice articulating your experience with AI technologies and scaling GTM programs.

• Company Research: Deeply understand Amazon's culture, particularly AWS's role in the cloud market and its commitment to AI innovation. Research the PACE team's mission and how partner engagement fits into AWS's broader GTM strategy.

⚠️ 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.