Ahmed U.

I deploy AI systems and cloud infrastructure directly into client environments — the kind of work that requires deep technical ownership and clear communication with non-engineering stakeholders. Whether it's LLM pipelines that ship to production, Kubernetes platforms ops teams can actually maintain, or DevOps transformations that stick, I focus on durable outcomes over clever architecture. I'm a senior platform and cloud engineer with hands-on experience across AWS, GCP, Kubernetes, Terraform, and AI/ML infrastructure. I've worked on systems supporting high-traffic applications, data and ML workloads, and regulated environments at companies like Deloitte and Thentia. My core strengths: - Forward deployment: embedding with client teams to deliver infrastructure end-to-end, not just recommend it - Deploying and operating AI/ML workloads on Kubernetes and managed cloud services (EKS, GKE, Vertex AI) - Building RAG pipelines, LLM agent infrastructure, and AI API integrations (OpenAI, Anthropic, AWS Bedrock) - Clean, production-ready IaC with Terraform and GitOps (ArgoCD) - CI/CD pipeline design and GitHub Actions automation - Observability, alerting, and on-call effectiveness (Datadog, Prometheus, Grafana) - Cloud cost optimization and capacity planning - Turning ambiguous requirements into clear, maintainable systems Recent work includes multi-environment infrastructure frameworks, Kubernetes platform standardization, CI/CD and deployment guardrails, observability strategies, and capacity optimization initiatives that reduced operational toil and improved developer velocity. NVIDIA-Certified Associate in AI Infrastructure and Operations. MS in Computer Science. Open to contract-to-hire engagements.