Senior Prototyping Engineer

📍 Job Overview

Job Title: Senior Prototyping Engineer

Company: Amazon

Location: Bogotá, D.C., Colombia

Job Type: Full-time

Category: Engineering / Cloud Services / Prototyping

Date Posted: August 3, 2026

Experience Level: 10+ years

Remote Status: On-site

🚀 Role Summary

• Architecting, developing, testing, and implementing loosely coupled distributed software solutions within an agile, AI-enabled development framework.

• Supporting AWS customers in building rapid Minimum Viable Product (MVP) experiments and prototypes aligned with their strategic vision for new products and services.

• Driving the AWS platform by bridging customer requirements with AWS service teams’ roadmaps, focusing on customers engaged in research, development, and innovation.

• Contributing to AWS customer-facing publications, such as white-papers and blogs, to share expertise and best practices in cloud prototyping and AI integration.

• Collaborating with multi-functional teams to leverage lean principles, iterative AI/GenAI powered agile development, and agentic approaches to deliver tangible technology and business outcomes.

📝 Enhancement Note: This role is deeply embedded within the AWS Prototyping and AI Customer Engineering (PACE) capability, focusing on hands-on development and customer engagement for innovation-driven use cases. The emphasis is on rapid development cycles, MVP experimentation, and delivering concrete business outcomes through cloud-native solutions.

📈 Primary Responsibilities

• Design and implement scalable, fault-tolerant, and loosely coupled distributed software systems that form the backbone of customer prototypes.

• Conduct in-depth research into emerging technological developments and apply them strategically to enhance customer engagements and prototype functionalities.

• Actively participate in customer engagements, translating their articulated strategic vision into actionable technical requirements for prototype development.

• Drive alignment between customer needs and the AWS service roadmap by providing feedback and insights to AWS service teams, influencing future platform development.

• Develop and deploy proof-of-concepts (POCs) and Minimum Viable Products (MVPs) that demonstrate the value of AWS services for innovation and new product development.

• Author and contribute to technical content, including white-papers, tutorials, and blog posts, that showcase successful customer implementations and best practices.

• Collaborate effectively within cross-functional teams, including developers, product managers, and customer stakeholders, to ensure successful project delivery.

• Travel to customer sites within the LATAM geography (0-25% of the time) to facilitate workshops, gather requirements, and present prototype progress.

📝 Enhancement Note: The responsibilities highlight a blend of deep technical expertise in distributed systems and cloud architecture with strong customer-facing consulting and communication skills. The focus is on rapid iteration and delivering measurable business value through advanced technologies like AI and GenAI.

🎓 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 requiring 10+ years of experience and advanced technical responsibilities.

Experience:

• A minimum of 10 years of IT development or implementation/consulting experience in the software or Internet industries.

• At least 7 years of experience in specific technology domain areas such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data & analytics.

• A minimum of 5 years of experience in designing, implementing, or consulting on applications and infrastructures.

• At least 2 years of hands-on programming experience.

• Proven experience presenting complex technical solutions and business outcomes to both technical and non-technical executive audiences. Required Skills:

• Distributed Systems Architecture: Expertise in designing, building, and deploying loosely coupled, scalable, and resilient distributed software solutions.

• Cloud Computing (AWS): Deep understanding and practical experience with the AWS platform, its services, and best practices for building cloud-native applications.

• Software Development Lifecycle: Proficiency across the entire software development lifecycle, including architecture, design, development, testing, and deployment.

• Agile Methodologies: Strong experience working within agile development frameworks, including iterative development, rapid prototyping, and lean principles.

• Artificial Intelligence & Generative AI: Familiarity and practical application of AI/GenAI concepts in developing innovative solutions and prototypes.

• Technical Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts clearly and concisely to diverse audiences.

• Problem-Solving: Demonstrated ability to analyze complex technical challenges and devise effective, innovative solutions.

• Customer Engagement: Experience in consulting or client-facing roles, understanding customer needs, and translating them into technical strategies.

Preferred Skills:

• AWS Solutions Architecture: Experience architecting and operating solutions built on the AWS platform.

• Prototyping & MVP Development: Proven track record of building rapid prototypes and MVPs to validate new product ideas and business models.

• Technical Writing: Experience authoring customer-facing publications like white-papers, tutorials, and blog posts.

• LATAM Market Knowledge: Understanding of the technology landscape and business needs within the Latin American region.

• Agentic Systems: Familiarity with agentic approaches in AI development.

📝 Enhancement Note: The extensive experience requirement (10+ years) suggests a need for seasoned professionals who can independently lead complex technical initiatives and mentor junior engineers. The emphasis on "specific technology domain areas" indicates a preference for deep expertise rather than broad, superficial knowledge.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies of Distributed Systems: Detailed examples of complex distributed systems designed and implemented, showcasing architecture, scalability, fault tolerance, and performance metrics.

• Prototyping & MVP Demonstrations: Evidence of successful rapid prototyping projects, highlighting the speed of development, innovation, and the business value delivered through MVPs.

• AWS Cloud Architecture Designs: Diagrams and explanations of solutions architected and deployed on AWS, demonstrating proficiency with key services and best practices.

• AI/GenAI Application Examples: Prototypes or projects that effectively leverage Artificial Intelligence or Generative AI to solve specific business problems or create new capabilities.

• Technical Publication Samples: Links or excerpts from white-papers, blog posts, or tutorials authored, showcasing technical depth and communication clarity.

Process Documentation:

• Workflow Design for Rapid Development: Documentation of methodologies used to design and optimize rapid development cycles for prototypes and MVPs.

• Implementation & Automation Strategies: Examples of how processes were implemented and automated to achieve efficiency and speed in prototype delivery.

• Measurement & Performance Analysis: Methods used to measure the performance of prototypes and the business impact of delivered solutions, including relevant metrics and KPIs.

📝 Enhancement Note: Given the role's focus on prototyping and customer engagement, a portfolio that clearly demonstrates hands-on technical execution, rapid iteration capabilities, and the ability to translate technical solutions into tangible business outcomes will be critical for evaluation.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for Senior Prototyping Engineers with 10+ years of experience in major technology hubs like Bogotá, and considering Amazon's compensation structure for similar roles, a competitive annual salary range is estimated between $80,000,000 - $150,000,000 COP. This range can vary based on specific experience, qualifications, and interview performance.

Benefits:

• Comprehensive Health Insurance: Medical, dental, and vision coverage.

• Retirement Savings Plan: Contributions to a pension or retirement fund.

• Stock Options/RSUs: Potential for Amazon Restricted Stock Units (RSUs) as part of the compensation package.

• Paid Time Off: Generous vacation days, sick leave, and public holidays.

• Professional Development: Access to training, certifications, conferences, and resources for continuous learning and career advancement.

• Mentorship Programs: Opportunities to learn from experienced professionals and grow within the organization.

• Employee Affinity Groups: Participation in employee-led groups that foster inclusion and community.

• Work-Life Harmony Initiatives: Support for maintaining a healthy balance between professional and personal life.

• Relocation Assistance: If applicable, support for relocation to Bogotá.

Working Hours: The standard working hours are typically 40 hours per week, Monday to Friday. However, given the nature of prototyping and customer engagements, flexibility may be required to meet project deadlines and customer needs.

📝 Enhancement Note: The salary estimate is based on research from Colombian job boards and global tech salary aggregators for comparable roles and experience levels in major cities. Benefits are standard for large tech organizations like Amazon, with a particular emphasis on professional growth and employee well-being as highlighted in the job description.

🎯 Team & Company Context

🏢 Company Culture

Industry: Cloud Computing / Internet Services / E-commerce & Technology. Amazon Web Services (AWS) is a leader in the global cloud computing market, providing a vast array of services that power businesses worldwide. The Prototyping and AI Customer Engineering (PACE) team operates at the forefront of cloud innovation, leveraging AI and GenAI to drive customer success.

Company Size: Amazon is a multinational technology company with over 1.5 million employees globally, operating in various sectors including e-commerce, cloud computing, digital streaming, and artificial intelligence. This large scale offers immense opportunities for career growth and exposure to diverse projects.

Founded: Amazon was founded in 1994 by Jeff Bezos. AWS was launched in 2006, becoming a foundational pillar of Amazon's business and a leader in the cloud infrastructure market. The company's culture is deeply rooted in customer obsession, innovation, and a long-term perspective.

Team Structure:

• PACE Capability: The Prototyping and AI Customer Engineering (PACE) capability is a specialized team within AWS focused on customer-facing innovation.

• Cross-functional Development: The team comprises developers, engineers, and potentially solution architects who work collaboratively to build prototypes and MVPs.

• Agile Environment: The team operates within an agile framework, emphasizing iterative development and rapid feedback loops.

• Reporting: While not explicitly detailed, roles at this level typically report to a manager or director within the AWS engineering or customer solutions organization, with significant autonomy in project execution.

Methodology:

• Lean Principles & Iterative Development: The team employs lean methodologies to minimize waste and maximize value, focusing on iterative cycles of build-measure-learn.

• AI/GenAI Powered Development: Integration of artificial intelligence and generative AI is core to the team's approach, enabling faster development and more sophisticated prototypes.

• Agentic Approaches: Utilizing agentic systems and multi-functional teams to drive autonomous or semi-autonomous problem-solving and development processes.

• Rapid MVP Experimentation: A primary focus on quickly building and testing Minimum Viable Products to validate concepts and gather user feedback.

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

📝 Enhancement Note: Amazon's culture, often described by its Leadership Principles (Customer Obsession, Ownership, Invent and Simplify, etc.), is highly influential. The PACE team embodies these principles through its focus on customer outcomes, rapid innovation, and proactive problem-solving.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a "Senior" level, indicating a high degree of technical expertise, experience, and the ability to lead significant aspects of projects independently. A Senior Prototyping Engineer is expected to be a subject matter expert in their domain, capable of architecting complex solutions, mentoring junior engineers, and influencing technical direction.

Reporting Structure: As a Senior Engineer, you would likely report to a Manager or Director within the AWS Prototyping and AI Customer Engineering organization. You would collaborate closely with customer stakeholders, AWS service teams, and potentially other senior engineers and architects.

Operations Impact: The impact of this role is directly tied to enabling AWS customers to innovate and launch new products and services faster. By building effective prototypes and MVPs, this engineer helps customers validate business ideas, secure investment, and accelerate their time-to-market, thereby driving adoption and revenue growth for AWS.

Growth Opportunities:

• Technical Specialization: Deepen expertise in specific AWS services, AI/GenAI technologies, or distributed systems architecture.

• Leadership Development: Progress to a Principal Engineer role, Technical Lead, or management positions within AWS engineering or customer solutions.

• Cross-functional Mobility: Opportunities to move into roles focused on product management, solution architecture, or broader engineering management within Amazon.

• Industry Influence: Contribute to open-source projects, speak at conferences, and author influential publications in the cloud and AI space.

• Advanced Training & Certifications: Access to Amazon's extensive learning resources, including advanced AWS certifications and specialized AI/ML training programs.

📝 Enhancement Note: Amazon is known for providing robust career development paths. For a Senior Prototyping Engineer, growth would involve deepening technical mastery, expanding leadership responsibilities, and potentially moving into strategic roles that shape AWS's future offerings for customers.

🌐 Work Environment

Office Type: This role is primarily on-site in Bogotá, D.C., implying a dynamic office environment where collaboration and hands-on work are central. Amazon offices are typically modern, equipped with state-of-the-art technology, and designed to foster innovation and teamwork.

Office Location(s): Bogotá, D.C., Colombia. Specific office details would be provided by HR, but major tech hubs generally offer convenient access via public transportation and proximity to amenities.

Workspace Context:

• Collaborative Spaces: The office environment will likely feature open workspaces, meeting rooms, and dedicated areas for brainstorming and team collaboration, crucial for agile prototyping.

• Access to Technology: Expect access to high-performance computing resources, development tools, and the full suite of AWS services for building and testing prototypes.

• Team Interaction: Frequent opportunities for direct interaction with team members, peers, and potentially customer representatives, facilitating rapid feedback and knowledge sharing.

• Innovation Hubs: Amazon offices often include spaces designed for experimentation and rapid development, supporting the core function of this role.

Work Schedule: While the standard is 40 hours per week, the nature of customer-facing prototyping and agile development may necessitate flexibility. This could include occasional extended hours to meet critical deadlines or support global customer needs, balanced by Amazon's commitment to work-life harmony.

📝 Enhancement Note: The on-site requirement in Bogotá suggests a focus on fostering a strong team dynamic and enabling close collaboration, which is particularly important for rapid prototyping and complex problem-solving.

📄 Application & Portfolio Review Process

Interview Process:

• Online Application & Screening: Initial review of your resume and application for alignment with basic qualifications.

• Hiring Manager/Recruiter Screen: A preliminary call to discuss your background, interest in the role, and high-level fit.

• Technical Interviews (Multiple Rounds): This will likely involve deep dives into your experience with distributed systems, AWS services, AI/GenAI, software development, and problem-solving. Expect coding challenges, system design questions, and scenario-based problem-solving.

• Portfolio Review/Presentation: A dedicated session where you will present selected case studies from your portfolio, demonstrating your technical achievements, process methodologies, and impact.

• Behavioral Interviews: Assessment of your alignment with Amazon's Leadership Principles through situational and behavioral questions.

• Final Round/Debrief: A concluding interview, potentially with senior leadership, to finalize assessment and discuss the role in more detail.

Portfolio Review Tips:

• Curate Effectively: Select 2-3 of your most impactful projects that best showcase your skills in distributed systems, AWS, AI/GenAI, and rapid prototyping. Prioritize projects with clear business outcomes.

• Structure Your Narrative: For each project, clearly articulate the problem statement, your role and contributions, the technical solutions implemented (architecture, technologies used), the challenges faced, and the measurable results or business impact.

• Highlight Process: Explain the development methodology used (e.g., agile, lean), how you approached rapid iteration, and how you managed complexity and risk.

• Quantify Impact: Use specific metrics (e.g., performance improvements, cost savings, time-to-market reduction, customer adoption rates) to demonstrate the value of your work.

• Technical Depth: Be prepared to dive deep into the technical details of your solutions, explaining architectural choices, trade-offs, and specific implementation details.

• Tailor to Role: Emphasize aspects of your work that align with AWS, AI/GenAI, and customer-facing innovation.

Challenge Preparation:

• System Design: Practice designing scalable, resilient, and distributed systems for various use cases. Focus on trade-offs and justifications for your design choices.

• Coding: Brush up on core data structures, algorithms, and programming paradigms relevant to distributed systems (e.g., Java, Python, Go).

• AWS Services: Review key AWS services relevant to building distributed applications and AI solutions (e.g., EC2, S3, Lambda, DynamoDB, SageMaker, Bedrock).

• Leadership Principles: Understand Amazon's Leadership Principles and prepare STAR method (Situation, Task, Action, Result) examples for each.

📝 Enhancement Note: Amazon's interview process is known for its rigor and focus on data-driven decision-making. A strong portfolio that clearly demonstrates technical competence, problem-solving ability, and tangible impact is crucial for success.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Proficiency in languages commonly used for distributed systems and cloud development, such as Python, Java,

Go, or C++.

• AWS Services: Extensive hands-on experience with core AWS services including:

  • Compute: EC2, Lambda, ECS, EKS
  • Storage: S3, EBS, EFS, Glacier
  • Databases: DynamoDB, RDS, Aurora, ElastiCache
  • Networking: VPC, Route 53, ELB, API Gateway
  • AI/ML: SageMaker, Bedrock, Comprehend, Rekognition, Translate
  • Developer Tools: CodeCommit, CodeBuild, CodeDeploy, CodePipeline

• Containerization: Docker, Kubernetes (EKS).

• Infrastructure as Code (IaC): CloudFormation, Terraform.

Analytics & Reporting:

• CloudWatch: For monitoring, logging, and performance analysis of AWS resources.

• Third-party Analytics Tools: Potentially experience with tools like Splunk, Datadog, or Grafana for advanced monitoring and visualization.

• Data Warehousing/Lakes: Experience with services like Redshift or Glue if data analysis is a significant part of prototype validation.

CRM & Automation:

• While not a direct CRM role, understanding how prototypes integrate with customer systems and workflows is beneficial. Experience with API integrations and workflow automation tools could be relevant.

📝 Enhancement Note: The technology stack is heavily AWS-centric. Expertise in core AWS services is non-negotiable, with a strong emphasis on services related to compute, storage, databases, networking, and increasingly, AI/ML. Familiarity with containerization and IaC is also highly valued.

👥 Team Culture & Values

Operations Values:

• Customer Obsession: Deeply understanding and working backward from customer needs to deliver innovative solutions that provide tangible business value.

• Invent and Simplify: Continuously seeking new ways to solve problems and improve processes, often through simplification and leveraging cutting-edge technology.

• Ownership: Taking full responsibility for projects and outcomes, acting with a sense of urgency and driving initiatives to completion.

• Bias for Action: Prioritizing execution and learning through rapid iteration and experimentation, rather than extensive deliberation.

• Dive Deep: Thoroughly analyzing problems and solutions, understanding the underlying technical details and business context.

• High Standards: Consistently striving for excellence in technical execution, customer solutions, and personal performance.

Collaboration Style:

• Cross-functional Integration: Working seamlessly with diverse teams (engineering, product, customer-facing) to achieve common goals.

• Data-Driven Decision Making: Relying on data and metrics to inform design choices, validate hypotheses, and measure success.

• Constructive Debate: Engaging in open and honest discussions to challenge ideas and arrive at the best solutions, always with respect for differing perspectives.

• Knowledge Sharing: Actively sharing insights, best practices, and lessons learned to foster a continuous learning environment within the team and the broader AWS community.

📝 Enhancement Note: Amazon's culture is defined by its Leadership Principles. Successful candidates will demonstrate an innate alignment with these principles, applying them to their daily work and interactions within the PACE team.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Pace of Innovation: Keeping up with the relentless evolution of AWS services and AI/GenAI technologies to ensure prototypes are cutting-edge.

• Complex Customer Requirements: Translating diverse and sometimes abstract customer needs into concrete, technically feasible prototype solutions.

• Balancing Speed and Quality: Achieving rapid development cycles without compromising the robustness, scalability, and security of the prototypes.

• Proving ROI for New Technologies: Demonstrating the tangible business value and return on investment for prototypes built using emerging AI/GenAI capabilities.

• Cross-Geographic Collaboration: Effectively collaborating with customers and internal teams across different time zones and cultural contexts within the LATAM region.

Learning & Development Opportunities:

• Cutting-Edge Technology Exposure: Direct experience with the latest AWS services and AI/GenAI advancements.

• Formal Training & Certifications: Access to Amazon's extensive learning platforms and support for obtaining advanced AWS certifications.

• Mentorship & Peer Learning: Opportunities to learn from and collaborate with highly experienced engineers and architects within AWS.

• Industry Conferences & Events: Potential to attend and present at leading technology conferences, contributing to industry knowledge.

• Career Path Exploration: Clear pathways for technical leadership, management, or specialization within AWS.

📝 Enhancement Note: The role presents significant challenges due to the dynamic nature of cloud technology and AI, but these challenges are directly tied to immense growth opportunities for individuals eager to be at the forefront of innovation.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex distributed system you designed and implemented. What were the key challenges, your architectural decisions, and the outcomes?"

  • Preparation: Have 1-2 detailed case studies ready, focusing on scalability, fault tolerance, and performance. Be prepared to discuss trade-offs and your specific contributions.

• "How would you approach building a rapid MVP for a customer looking to leverage GenAI for customer support? What AWS services would you consider and why?"

  • Preparation: Research current GenAI applications in customer support, understand relevant AWS services (e.g., Bedrock, Lambda, API Gateway, SageMaker), and outline a step-by-step prototyping process.

• "Tell me about a time you had to simplify a complex technical problem for a non-technical audience. How did you ensure they understood and agreed with your proposed solution?"

  • Preparation: Draw on experience presenting to executives. Focus on clear communication, business impact, and ensuring alignment. Company & Culture Questions:

• "Why are you interested in Amazon and specifically this role within AWS PACE?"

  • Preparation: Research Amazon's Leadership Principles, AWS's mission, and the PACE team's function. Connect your career goals and skills to the role and company values.

• "Describe a situation where you had to demonstrate 'Invent and Simplify' or 'Dive Deep' in a previous role."

  • Preparation: Prepare STAR method answers that clearly illustrate your understanding and application of these principles.

• "How do you ensure high standards in your work, especially when working under tight deadlines?"

  • Preparation: Discuss your personal quality assurance processes, attention to detail, and strategies for maintaining excellence in a fast-paced environment. Portfolio Presentation Strategy:

• Storytelling: Frame your portfolio projects as compelling stories of problem-solving and innovation. Start with the customer's challenge and end with the delivered business value.

• Visual Aids: Use diagrams, architecture charts, and simple mockups to illustrate your technical solutions effectively. Keep slides clean and focused.

• Quantifiable Results: Emphasize metrics and quantifiable outcomes. Be ready to explain how you measured success and what the impact was.

• Technical Depth on Demand: Be prepared to answer detailed technical questions about your projects, demonstrating your expertise and decision-making process.

• Focus on Collaboration: Highlight instances where you collaborated effectively with team members, customers, or other stakeholders.

📝 Enhancement Note: Amazon's interview process is designed to assess both technical prowess and cultural fit. Practicing with the STAR method for behavioral questions and being able to articulate your technical contributions with clear, quantifiable results will be key.

📌 Application Steps

To apply for this Senior Prototyping Engineer position:

• Submit your application through the Amazon Jobs portal at https://www.amazon.jobs/en/jobs/10490786.

• Tailor your Resume: Customize your resume to highlight experience in distributed systems, AWS, AI/GenAI, rapid prototyping, and customer-facing roles. Use keywords from the job description and emphasize achievements with quantifiable results.

• Prepare Your Portfolio: Select 2-3 strong case studies that showcase your most relevant projects. Ensure each case study clearly outlines the problem, your solution, the technologies used (especially AWS and AI/GenAI), and the business impact.

• Practice Interview Questions: Rehearse answers to common technical, behavioral, and system design questions, focusing on Amazon's Leadership Principles and the STAR method.

• Research Amazon & AWS: Deepen your understanding of Amazon's culture, its Leadership Principles, and the specific work of the AWS PACE team. Familiarize yourself with current trends in cloud computing and AI.

⚠️ 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.