As organizations move from cloud adoption to building AI-powered platforms, the role of experienced cloud architects has never been more important. Modern cloud environments demand not only technical expertise, but also the ability to design secure, scalable and production-ready architectures that enable innovation at enterprise scale.
To recognize professionals who consistently contribute to the AWS community, share knowledge, and help customers succeed, Amazon Web Services runs the AWS Ambassador program—one of its highest individual recognitions for technical leaders within AWS Partners.
This distinction is awarded to professionals who demonstrate technical excellence, active community engagement, customer impact, and continuous contribution to the AWS ecosystem.
This year, Sergio Cambelo, Cloud Architect at Keepler Data Tech, has joined this select group of AWS Ambassadors, reinforcing both his personal commitment to the cloud community and Keepler’s continued leadership in designing advanced cloud and AI solutions.
Sergio Cambelo, Cloud Architect at Keepler and AWS Ambassador. Passionate about designing cloud architectures, continuous learning, and sharing knowledge to help organizations and professionals get the most out of AWS.
What professional value does becoming an AWS Ambassador bring?
Being an AWS Ambassador creates value on several levels. The most immediate is access to a community of highly qualified professionals—architects and specialists who work extensively with AWS across a wide range of industries and business contexts. This leads to technical discussions at a level that is difficult to find elsewhere, while also providing a trusted network of experts whenever you face complex challenges. Beyond the community itself, the program also carries significant recognition. Becoming an Ambassador is not something you achieve simply by passing an exam. It is recognition based on real contributions: publishing technical content, delivering talks, actively participating in the community, and generating direct business value through customer engagement and capability building within the organization. It reflects a professional journey and long-term commitment, not just technical knowledge. From a practical perspective, the program also opens doors that would otherwise be difficult to access, including early visibility into new AWS services, participation in flagship events, and direct engagement with AWS product teams.
What impact do you think this recognition has for the company?
The impact an AWS Ambassador brings to the company is significant in several ways. I see the role as complementary to that of the Partner Manager. While the Partner Manager manages the commercial relationship with AWS, the Ambassador strengthens the technical and community dimension. Together, they provide a complete relationship with AWS. However, the greatest impact for Keepler lies in strengthening technical credibility with customers. AWS Partner competencies and designations demonstrate the organization’s collective capabilities—certifications, proven customer success, and validated methodologies. The Ambassador complements that corporate recognition by adding a visible, trusted individual who represents those capabilities within the broader AWS community. That creates real value in everyday customer interactions. When organizations evaluate partners, they don’t only look at logos or partnership tiers—they also look for the people behind them. The Ambassador becomes that trusted technical reference.
As an AWS Ambassador, what are your expectations for the coming year as you continue growing as an AWS specialist?
For me, the coming year will be shaped by the evolution of agentic systems applied to cloud operations—a trend that has already gained momentum this year and that I believe will accelerate significantly.
Cloud operations generate an enormous volume of signals, events, and repetitive decisions that simply do not scale with people alone. Automated remediation, continuous cost optimization, compliance management, incident response—these are all areas where an intelligent agent, equipped with the right APIs and reasoning capabilities, can act faster and more consistently than traditional manual processes. This is no longer classic automation based on runbooks or Lambda functions; we are talking about systems capable of understanding context and making informed decisions.
The timing is right because the tooling is maturing. Services such as Amazon Bedrock Agents and frameworks like Strands are beginning to provide the patterns required to deploy these capabilities in production with confidence, including action traceability, human-in-the-loop workflows for critical decisions, and configurable guardrails.
The biggest challenge, however, is not technical—it is governance. Operating AI agents in production cloud environments raises entirely new questions. What permissions should an agent have? How do you audit its actions? How do you prevent a poorly configured agent from creating real operational impact? The intersection between agentic AI and cloud governance is where I want to focus my specialization over the next year, and where I believe some of the most exciting work lies ahead.
What advice would you give to people who are currently learning or specializing in AWS? What path would you recommend?
I don’t believe there is a single path to becoming an AWS specialist, and I’m generally skeptical of anyone who claims there is.
The first thing I would recommend is choosing an area that genuinely interests you. Developing deep technical expertise requires sustained effort over time, and that becomes much easier when you’re passionate about the subject.
Secondly—and, in my opinion, most importantly—nothing replaces working on real projects. Courses and workshops certainly have their place, particularly when learning new services or organizing concepts, but genuine learning happens when you face real problems with real constraints. When something doesn’t work as expected, when you need to make design decisions with incomplete information, or when a customer has a deadline—that is where experience is built.
My practical advice is to actively seek those opportunities. If you’re just getting started, don’t wait for the perfect project. Even building real solutions in your own sandbox environment will teach you far more than earning multiple certifications back-to-back. Certifications are valuable as learning milestones and professional credentials, but the knowledge that truly stays with you comes from building, breaking, and fixing things yourself.
Can you share a cloud challenge you’re particularly proud of solving?
One of the most rewarding challenges I’ve worked on—and one that remains an ongoing journey—has been expanding an enterprise Landing Zone into a new AWS Region. It’s a challenge with two equally demanding dimensions, and I think that combination perfectly represents what enterprise cloud architecture is really about.
From a technical perspective, these projects involve highly complex environments with many moving parts: multiple AWS accounts, hybrid connectivity, DNS architecture, traffic inspection, route propagation… Every design decision creates downstream consequences. There is rarely a single correct answer; instead, success depends on balancing trade-offs and knowing when a solution is good enough versus when it deserves further refinement.
At the same time, the organizational challenge is just as demanding, if not more so. In large enterprises, initiatives like this involve many teams with different priorities and objectives. Managing expectations, aligning stakeholders, and explaining complex technical decisions in ways that make sense to different audiences require a completely different set of skills—skills that cannot be learned from books or certifications, only through experience.
I’m particularly proud of this challenge because it combines both dimensions. Solving a technically complex problem is rewarding, but doing so while coordinating a large organization and keeping the project moving forward is what truly helps you grow as a professional.
How important is AWS specialization for AI professionals?
Extremely important, and I believe this is still underestimated across much of the industry.
Artificial Intelligence does not exist in isolation—it depends on infrastructure. Training models, running inference workloads, securing data, scaling systems, and optimizing costs all require a robust cloud foundation.
AWS has positioned itself exceptionally well by providing a comprehensive platform that enables AI professionals to build and operate production-ready systems with confidence. However, taking full advantage of that platform requires deep technical knowledge: understanding which services fit each use case, designing architectures that scale efficiently, controlling inference costs as workloads grow, and implementing the right security and governance controls.
An AI professional who lacks an understanding of the infrastructure layer inevitably reaches a limit. They may be capable of building models and pipelines, but when it comes to deploying them sustainably, securely, and at enterprise scale, that knowledge gap quickly becomes apparent. AWS specialization is no longer simply an additional skill for AI professionals—it has become an essential part of the complete profile.
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