Prototyping Architect, PACE

📍 Job Overview

Job Title: Prototyping Architect, PACE

Company: Amazon Web Services (AWS)

Location: Belo Horizonte, Minas Gerais, Brazil & São Paulo, São Paulo, Brazil

Job Type: Full-Time

Category: Solutions Architecture / Engineering (with a focus on Prototyping and AI/ML)

Date Posted: 2026-03-31

Experience Level: 10+ years

Remote Status: On-site

🚀 Role Summary

• Architect, develop, test, and implement advanced, loosely coupled distributed software solutions leveraging cutting-edge technologies.

• Drive innovation by researching and deploying the latest technological developments in customer engagements, particularly within AI/ML and emerging fields.

• Act as a key liaison between customer requirements and AWS service roadmaps, influencing product development and platform strategy.

• Focus on rapid, time-boxed prototyping engagements to demonstrate the art of the possible with AWS services and translate bold ideas into tangible business value.

• Contribute to AWS customer-facing publications, sharing expertise through white-papers, tutorials, and blogs to educate and empower the broader community.

📝 Enhancement Note: While this role is titled "Prototyping Architect," its core functions heavily lean into hands-on software engineering, solution architecture, and deep technical expertise in AI/ML. The "PACE" designation (Prototyping and AI Customer Engineering) underscores a specialized, customer-facing engineering function within AWS, distinct from traditional sales-focused Solutions Architects. The emphasis is on building and demonstrating, not just consulting.

📈 Primary Responsibilities

• Design and build robust, scalable, and maintainable distributed software systems using best practices to ensure prototypes can serve as a foundation for production solutions.

• Develop and implement prototypes utilizing Agentic AI, Machine Learning, Deep Learning, Generative AI, IoT, and Serverless Architectures to address complex customer challenges.

• Collaborate closely with customers to understand their unique business problems and translate them into innovative technical solutions through rapid experimentation.

• Engage in deep-dive education and design exercises to create world-class solutions built on the AWS platform.

• Actively participate in the agile development process, embracing a culture of high-judgment failure and fast iteration to accelerate innovation.

• Author and contribute to high-quality customer-facing content, including white-papers, tutorials, and blog posts, to disseminate knowledge and best practices.

• Drive customer adoption of AWS services by aligning their technical requirements with the strategic roadmaps of AWS service teams.

• Travel up to 25% to customer sites and industry events, fostering relationships and demonstrating technical capabilities.

📝 Enhancement Note: The responsibilities highlight a dual focus on deep technical execution (architecting, developing, testing) and strategic influence (driving AWS platform, aligning roadmaps). The emphasis on "loosely coupled distributed software solutions" and specific AI/ML technologies indicates a need for modern, cloud-native development skills.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field is typically expected for roles of this seniority and technical depth within AWS.

Experience:

• A minimum of 10+ years of comprehensive experience in IT development, implementation, or consulting within the software or Internet industries.

• At least 4+ years of specialized experience in specific technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data & analytics.

Required Skills:

• Proven expertise in Software Engineering principles and practices, with a strong ability to write clean, efficient, and maintainable code.

• Deep understanding and practical experience in Solution Architecture, particularly for distributed systems and cloud-native applications.

• Demonstrated experience in Prototyping and rapid development cycles to validate new ideas and technologies.

• Hands-on experience with AI/ML technologies, including Machine Learning, Deep Learning, and Generative AI concepts and applications.

• Proficiency in developing and deploying solutions using Serverless Architectures and related AWS services.

• Strong understanding of Cloud Computing concepts, with a focus on the AWS ecosystem.

• Experience with Distributed Software Solutions architecture and implementation.

Preferred Skills:

• Experience working within software development or Internet-related industries, understanding their unique challenges and workflows.

• Practical experience working with AWS technologies from a development and/or operations (DevOps) perspective.

• Expertise in Agentic AI and the development of intelligent agent-based systems.

• Experience with IoT (Internet of Things) solutions and their integration.

• Knowledge of Systems Engineering, Infrastructure design, Security, and Networking principles within a cloud context.

• Experience authoring technical content such as white-papers, tutorials, and blogs.

📝 Enhancement Note: The "10+ years" of IT experience, combined with specific domain requirements, signifies a senior-level role demanding a blend of broad IT knowledge and deep specialization in modern technologies like AI/ML. The preference for AWS experience from a dev/ops perspective suggests that candidates who have operationalized cloud solutions will be highly valued.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase of prototypes developed, demonstrating innovative application of AI/ML, Generative AI, or other advanced technologies on cloud platforms.

• Examples of distributed software solutions designed and implemented, highlighting scalability, resilience, and architectural patterns.

• Case studies detailing the process of problem identification and the translation of customer requirements into working technical solutions.

• Demonstrations of system implementation projects, emphasizing the integration of various AWS services and third-party tools.

Process Documentation:

• Detail workflows for rapid prototyping, including ideation, design, development, testing, and iteration phases.

• Document the process for researching and deploying new technologies, including evaluation criteria and implementation strategies.

• Outline methodologies for aligning customer requirements with AWS service roadmaps, demonstrating impact and influence.

• Showcase approaches to data analysis and insight generation used in the development of AI/ML models and prototypes.

• Describe the process for ensuring prototypes provide a foundation for production solutions, including considerations for scalability, security, and maintainability.

📝 Enhancement Note: For a role centered on prototyping and customer engineering, a portfolio is crucial. It should not just list projects but demonstrate the process of innovation, problem-solving, and technical execution, particularly in the context of rapid development and emerging technologies. The emphasis is on showing how solutions were built and why specific technologies were chosen.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for senior Solutions Architects and Engineering roles with 10+ years of experience in major tech hubs like São Paulo and Belo Horizonte, along with the specialized AI/ML focus, the estimated annual salary range for this position is likely between R$300,000 to R$600,000 BRL (Brazilian Real). This estimate is highly dependent on the candidate's specific experience, negotiation, and the internal Amazon compensation bands for this role and location.

Benefits:

• Comprehensive health, dental, and vision insurance plans.

• Generous paid time off (PTO), including vacation, sick leave, and holidays.

• Retirement savings plan (e.g., employee pension plan with company matching).

• Stock options or Restricted Stock Units (RSUs) as part of the compensation package, reflecting Amazon's performance-driven culture.

• Professional development opportunities, including access to training, certifications, and conferences relevant to AI/ML and cloud technologies.

• Employee discount on Amazon products and services.

• Relocation assistance may be provided for candidates relocating to Brazil.

• Opportunities for internal mobility and career advancement within AWS globally.

Working Hours: The standard working hours are typically 40 hours per week. However, given the nature of prototyping and customer engagements, there may be flexibility required to meet project deadlines and customer needs, potentially involving occasional work outside standard business hours.

📝 Enhancement Note: Salary estimations for Brazil are based on research from reputable job boards and salary aggregators for senior tech roles in São Paulo and Belo Horizonte, factoring in the specialized nature of AI/ML and Solutions Architecture. Benefits are standard for large, multinational tech companies like Amazon.

🎯 Team & Company Context

🏢 Company Culture

Industry: Cloud Computing Services (Technology). Amazon Web Services (AWS) is a global leader in providing on-demand cloud computing platforms and APIs, offering a vast array of services including computing power, storage, and content delivery at scale.

Company Size: Amazon is a multinational technology company with over 1.5 million employees worldwide. AWS itself is a significant division within Amazon, employing tens of thousands of highly skilled professionals.

Founded: Amazon was founded in 1994 by Jeff Bezos, and AWS was launched in 2006. The company has a long history of innovation and customer obsession.

Team Structure:

• The Prototyping and AI Customer Engineering (PACE) team is described as an "elite group of hands-on builders." This suggests a relatively small, specialized, and highly skilled team operating within the broader AWS organization.

• Team members likely report to a manager or director focused on customer engineering or solutions architecture. The structure is likely project-oriented, with team members assigned to specific customer engagements.

Methodology:

• Data Analysis and Insights: PACE teams leverage customer data and technical insights to inform prototype development and demonstrate business value.

• Workflow Planning and Optimization: The team focuses on rapid, time-boxed prototyping engagements, requiring efficient workflow planning and continuous optimization to deliver results quickly.

• Automation and Efficiency: Utilizing AWS services and modern development practices to automate processes and maximize efficiency in prototype creation and deployment.

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

📝 Enhancement Note: The description of PACE as "elite" and "hands-on builders" implies a high-performance culture focused on technical excellence and rapid execution. The company's "customer obsession" and "work hard, have fun, make history" credo are central to its operational ethos.

📈 Career & Growth Analysis

Operations Career Level: This role represents a senior individual contributor (IC) position within the technical track of AWS. It sits at a level where deep technical expertise is paramount, and the individual is expected to operate with a high degree of autonomy, driving complex projects and influencing technical direction. This is beyond a standard "Solutions Architect" and leans towards a specialized "Principal Engineer" or "Staff Engineer" with a prototyping and customer-facing mandate.

Reporting Structure: The Prototyping Architect will likely report to a Manager or Director within the Prototyping and AI Customer Engineering (PACE) organization. While the role is hands-on, collaboration with other senior engineers, architects, and customer-facing teams is expected.

Operations Impact: The primary impact of this role is on customer success and innovation. By building tangible prototypes, the Prototyping Architect directly influences customer adoption of AWS services, helps them explore new markets and business models, and validates the potential of emerging technologies like Generative AI and Agentic AI. This role is critical in demonstrating the practical application and business value of AWS's cutting-edge offerings.

Growth Opportunities:

• Technical Specialization: Deepen expertise in specific AI/ML domains, Agentic AI, or emerging cloud technologies, becoming a recognized subject matter expert within AWS.

• Leadership Progression: Transition into leadership roles such as Principal Architect, Staff Engineer, or management positions within engineering or solutions architecture teams.

• Cross-Functional Mobility: Move into roles within AWS service teams, product management, or strategic customer engagement divisions.

• Mentorship: Mentor junior engineers and architects, sharing knowledge and best practices in prototyping and cloud-native development.

• Industry Influence: Contribute to industry standards, speak at conferences, and publish influential technical content.

📝 Enhancement Note: The "10+ years" experience requirement clearly places this role at a senior individual contributor level. Growth opportunities are geared towards deepening technical mastery, moving into higher-level technical leadership, or transitioning into strategic roles that leverage their deep understanding of customer needs and AWS capabilities.

🌐 Work Environment

Office Type: This is an on-site role, implying a traditional office environment within Amazon's Brazilian offices in Belo Horizonte or São Paulo. These offices are typically modern, well-equipped, and designed to foster collaboration.

Office Location(s):

• Belo Horizonte, Minas Gerais, Brazil

Workspace Context:

• Collaborative Environment: Expect an open-plan office setting or dedicated team spaces designed to encourage interaction, brainstorming, and knowledge sharing among engineers, architects, and potentially other customer-facing roles.

• Operations Tools and Technology: Access to high-performance computing resources, development tools, and a wide range of AWS services will be readily available to facilitate prototype development.

• Team Interaction: Opportunities for regular interaction with the PACE team, other AWS engineers, and direct engagement with customer technical teams, allowing for a dynamic and intellectually stimulating work environment.

Work Schedule: The role adheres to standard business hours (likely 40 hours/week) but may require flexibility to accommodate project deadlines, customer needs, and time zone differences when collaborating internationally. The culture emphasizes delivering results, which can sometimes necessitate working beyond typical hours.

📝 Enhancement Note: While on-site, the nature of the role involves significant customer interaction, which might include remote collaboration or occasional travel. The office environment is expected to be conducive to intense technical work and collaborative problem-solving.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will likely conduct an initial phone screen to assess basic qualifications, experience, and cultural fit.

• Technical Phone Screen(s): Expect one or more technical interviews focusing on core engineering principles, distributed systems, cloud architecture, and potentially AI/ML concepts.

These may involve coding exercises or system design questions.

• On-site/Virtual Loop: A series of interviews (typically 4-6) with various team members, including engineers, architects, and potentially the hiring manager. This loop will cover:

  • Deep Technical Dive: In-depth discussions on your experience with AI/ML, Generative AI, prototyping, and distributed systems.
  • System Design: Designing complex, scalable systems, often with an emphasis on cloud-native architectures and specific AWS services.
  • Coding/Problem-Solving: Practical coding challenges or algorithmic problem-solving exercises.
  • Customer Engagement Scenarios: How you would approach customer problems, build rapport, and demonstrate technical solutions.
  • Behavioral Questions: Assessing your alignment with Amazon's Leadership Principles, such as Customer Obsession, Bias for Action, Dive Deep, and Invent and Simplify.

• Portfolio Presentation: You may be asked to present specific projects or prototypes from your portfolio, detailing the problem, your solution approach, the technologies used, and the impact.

Portfolio Review Tips:

• Curate Selectively: Focus on 2-3 of your most impactful and relevant projects that showcase your skills in prototyping, AI/ML, and distributed systems architecture.

• Structure Your Case Studies: For each project, clearly articulate:

  • The Problem: What was the customer's challenge or business need?
  • Your Role & Contribution: What specifically did you do?
  • The Solution: Describe the architecture, technologies (especially AWS services, AI/ML), and design choices.
  • The Process: How did you approach prototyping, iteration, and development?
  • The Outcome/Impact: What were the results? Quantify wherever possible (e.g., performance improvements, cost savings, new capabilities demonstrated).

• Highlight AWS Expertise: Emphasize your experience with relevant AWS services (e.g., SageMaker, EC2, Lambda, S3, Bedrock, etc.) and how they were utilized.

• Demonstrate "Art of the Possible": Show how your prototypes explored new frontiers and demonstrated innovative applications of technology.

• Be Prepared for Deep Dives: Anticipate detailed questions about your technical decisions, trade-offs, and challenges faced.

Challenge Preparation:

• System Design Practice: Practice designing scalable, fault-tolerant distributed systems. Consider common AWS patterns and services.

• Coding Proficiency: Brush up on data structures, algorithms, and coding in a language commonly used in cloud development (e.g., Python, Java, Go).

• AI/ML Fundamentals: Review core concepts of Machine Learning, Deep Learning, and Generative AI. Be ready to discuss model training, deployment, and common use cases.

• Amazon Leadership Principles: Prepare specific examples from your career that demonstrate each of Amazon's Leadership Principles. Use the STAR method (Situation, Task, Action, Result).

📝 Enhancement Note: Amazon's interview process is known for its rigor and focus on Leadership Principles. Candidates must be prepared for deep technical dives and detailed behavioral assessments. A strong portfolio demonstrating hands-on building and innovative problem-solving is essential for this specific role.

🛠 Tools & Technology Stack

Primary Tools:

• AWS Services: Extensive use of various AWS services is expected, including but not limited to:

  • AI/ML: Amazon SageMaker, Amazon Bedrock, Amazon Rekognition, Amazon Comprehend, Amazon Personalize.
  • Compute: EC2, Lambda, ECS, EKS.
  • Storage: S3, EBS, RDS, DynamoDB.
  • Networking: VPC, Route 53, ELB.
  • Developer Tools: CodeCommit, CodeBuild, CodeDeploy, CodePipeline.
  • Containers: Docker, Kubernetes (EKS).

• Programming Languages: Proficiency in languages like Python (highly preferred for AI/ML and scripting), Java, Go, Node.js.

• Development Frameworks: Experience with relevant frameworks for building distributed applications and APIs.

Analytics & Reporting:

• AWS Analytics Services: CloudWatch for monitoring and logging, AWS Data Pipeline, potentially services like Redshift or Athena for data warehousing and querying.

• Visualization Tools: Experience with tools for dashboarding and reporting may be beneficial, though not explicitly stated as a primary requirement.

CRM & Automation:

• While not a direct CRM role, understanding how prototypes integrate with or influence customer CRM systems (e.g., Salesforce) may be relevant in customer engagements.

• CI/CD Tools: Familiarity with continuous integration and continuous delivery pipelines for automating software releases.

• Infrastructure as Code (IaC): Experience with tools like AWS CloudFormation or Terraform for provisioning and managing infrastructure.

📝 Enhancement Note: The technology stack is heavily AWS-centric, with a strong emphasis on AI/ML services. Candidates should be adept at leveraging the breadth of AWS offerings to build sophisticated prototypes. Proficiency in Python is almost a given for this role.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: A deep commitment to understanding and meeting customer needs, driving the development of solutions that deliver tangible business value.

• Bias for Action: A willingness to move fast, experiment, and take calculated risks to achieve results, embracing iterative development.

• Invent and Simplify: A drive to innovate and find creative solutions, while also simplifying complex problems and processes for efficiency and scalability.

• Dive Deep: A commitment to understanding systems and details at a profound level, enabling informed decision-making and robust problem-solving.

• Ownership: Taking full responsibility for projects and outcomes, demonstrating accountability and a proactive approach.

Collaboration Style:

• Cross-Functional Integration: Actively collaborating with customers, AWS service teams, and internal stakeholders to ensure alignment and successful project outcomes.

• Process Review Culture: A willingness to continuously evaluate and improve development and prototyping processes, seeking feedback and incorporating best practices.

• Knowledge Sharing: A culture of open communication and knowledge sharing, where expertise in AI/ML, prototyping, and cloud technologies is readily disseminated through discussions, documentation, and presentations.

📝 Enhancement Note: The values reflect Amazon's core Leadership Principles, which permeate all levels and teams within the company. For this role, these values translate into a proactive, customer-focused, and technically rigorous approach to building innovative solutions.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Technology Evolution: Keeping pace with the incredibly fast-moving fields of AI/ML, Generative AI, and cloud computing requires continuous learning and adaptation.

• Balancing Speed and Quality: The need to build prototypes rapidly while ensuring they are robust enough to inform production decisions presents a constant challenge.

• Complex Customer Needs: Addressing diverse and often ambiguous customer requirements with innovative yet practical solutions.

• Translating Vision to Reality: Effectively demonstrating the "art of the possible" through tangible prototypes that clearly show business value.

Learning & Development Opportunities:

• Specialized Training: Access to AWS training, certifications, and internal resources focused on the latest advancements in AI/ML, distributed systems, and cloud architecture.

• Industry Conferences: Opportunities to attend and present at leading technology conferences, staying abreast of industry trends and networking with peers.

• Mentorship Programs: Being mentored by senior engineers and architects within AWS, and potentially mentoring junior team members, fostering skill development and leadership growth.

• Exposure to Cutting-Edge Projects: Working on highly innovative projects at the forefront of technology with global customers.

📝 Enhancement Note: The role is designed for individuals who thrive in dynamic environments and enjoy tackling complex technical challenges. The growth opportunities are significant, offering a clear path for technical leadership and specialized expertise within the cloud and AI domains.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex distributed system you architected or significantly contributed to. What were the key design considerations, trade-offs, and challenges you faced?" (Focus on scalability, resilience, and specific AWS services.)

• "Walk me through a prototype you built using AI/ML or Generative AI. What problem did it solve, what was your approach to development, and what was the outcome?" (Be ready to discuss the data, models, and deployment.)

Company & Culture Questions:

• "How do you embody Amazon's Leadership Principle of 'Customer Obsession' in your work?" (Provide a specific example.)

• "Describe a time you had to 'Invent and Simplify' to solve a technical challenge." (Highlight innovation and efficiency.)

Portfolio Presentation Strategy:

• Start with the 'Why': Clearly articulate the business problem or customer need that drove the project.

• Show, Don't Just Tell: Use diagrams, code snippets (if appropriate), or demos to illustrate your solutions.

• Quantify Impact: Wherever possible, use metrics to demonstrate the success of your prototypes (e.g., performance gains, cost reductions, new functionalities enabled).

• Highlight Your Role: Be specific about your contributions, especially if it was a team project.

• Discuss Trade-offs: Be prepared to explain why you made certain technical decisions and what alternatives you considered.

📝 Enhancement Note: Amazon interviews are rigorous and focus on both technical depth and behavioral alignment. Practice articulating your experience using specific examples that map to their Leadership Principles. A well-prepared portfolio presentation is crucial for this role.

📌 Application Steps

To apply for this Prototyping Architect position:

• Submit your application through the official Amazon Jobs portal.

• Tailor your resume: Highlight your experience with AI/ML, Generative AI, distributed systems, cloud architecture (especially AWS), and prototyping. Quantify your achievements with specific metrics and impact.

• Prepare your portfolio: Select 2-3 key projects that best demonstrate your skills in building and architecting innovative solutions, focusing on the "art of the possible" with AWS technologies.

• Practice interview questions: Prepare for technical deep dives, system design challenges, and behavioral questions based on Amazon's Leadership Principles, using the STAR method.

• Research AWS PACE: Understand the team's mission and how your skills and experience align with their focus on rapid prototyping and customer engineering.

⚠️ 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.