Guillermo Ruiz

Sr. GTM Specialist Solutions Architect, Efficient Compute @ AWS | Helping Engineering Leaders Design Efficient AI & Confidential Compute Architectures | Grafana Champion & Arm Ambassador

Amazon Web Services (AWS)ex-Universidad Rey Juan Carlosex-Computer Sciences Corporation (CSC)

“

Cloud costs keep rising. AI infrastructure is becoming more complex, while engineering leaders are still asked to do more with

More

I know that world firsthand. After co-founding a startup and working as an infrastructure engineer, I became obsessed with solving the tension between innovation and efficiency. Along the way, I’ve built AIOps platforms, designed sentiment analysis systems for the gaming industry (PlayStation), and explored augmented reality for data center Today, as a Sr. GTM Specialist Solutions Architect in the Efficient Compute team at AWS, I help organizations design AI infrastructure that is efficient, secure, and measurable (from the underlying compute architecture to how models are served in My work sits at the intersection of AI infrastructure, inference engineering, confidential computing, and performance One principle drives much of my work: not every AI workload needs a GPU. The right architecture depends on latency, throughput, model characteristics, utilization, security, and Core focus areas:- Inference Engineering: CPU-based model serving, RAG, benchmarking, and price-performance - Confidential Computing: Nitro Enclaves, TPM, attestation, cryptographic isolation, and hardware-rooted trust for sensitive AI - Efficient Compute: Graviton, Spot, Karpenter, and architectures that improve utilization and performance per - Performance Engineering & Observability: profiling, benchmarking, microarchitectural analysis, and telemetry-driven I also share what I learn as an international speaker, technical writer, and co-host of Charlas Técnicas de AWS, ranked in the Top 10%. I’m a Grafana Champion and Arm Developer Ambassador, and previously VMware vExpert, Cisco Champion, and HashiCorp And my secret passion? Space. I build side projects to observe satellites, measure starlight, and experiment with efficient compute and AI at the edge. Because sometimes the best way to understand infrastructure is to give yourself a ridiculous engineering problem to My mission: make efficient AI infrastructure, performance engineering, and confidential computing the default, not the 👉🏻 If you’re a CTO, architect, or engineering leader rethinking how AI runs in production, let’s connect.