Saurabh Singhal

About Saurabh Singhal

I am a Cloud, DevOps and GenAI transformation leader with 16+ years of experience building and scaling platform engineering, automation and cloud modernization programs for global enterprises. I specialize in architecting multi-region AWS platforms, leading DevOps operating model adoption, and integrating GenAI into CI/CD, observability and incident response to improve release velocity, system reliability, and cloud cost efficiency.I have led multi-million-dollar cloud initiatives, delivered 100+ production releases, built DevOps Centers of Excellence, and coached engineering and architecture teams across India, UK, Europe and the US. My work has reduced deployment cycles from weekly to under an hour, improved platform uptime to 99.99%, and cut cloud spend by up to 30% through governance, automation, and FinOps alignment.On the technical side, I work hands-on with AWS, Kubernetes/EKS, Terraform, GitOps, distributed systems design, SRE practices, and AI-augmented automation. On the GenAI side, I design and implement Bedrock-based architectures, RAG systems, LLM workflow automation,Agentic AI model evaluation guardrails, and platform-integrated AI assistants for ops and engineering teams.I operate at the intersection of architecture, execution, and leadership — enabling teams to move from tooling to platforms, from automation to intelligence, and from cloud adoption to cloud value realization.

Experience

1. Solutions Architect

   Amazon Web Services (AWS)

   Jul 2024 — Present · Gurugram, IN

   Lead the design and delivery of enterprise-scale Generative AI and Agentic AI solutions, driving business transformation through LLM-powered applications and intelligent automation.• Architect and deploy production-grade LLM-based applications and Autonomous Agentic Systems, enabling task planning, decomposition, memory management, and tool/API orchestration.• Design and implement RAG (Retrieval-Augmented Generation) pipelines using vector databases, embeddings, and advanced prompt engineering to improve factual grounding and response quality.• Build end-to-end GenAI solutions leveraging LLMs, LangChain, multi-agent frameworks, and orchestration layers to solve complex real-world business problems.• Lead cloud-based AI deployments across Azure OpenAI and GCP Vertex AI, ensuring scalability, high availability, performance optimization, and cost efficiency.• Define GenAI solution architecture patterns, governance frameworks, responsible AI practices, and enterprise AI adoption strategies.• Implement robust MLOps / LLMOps pipelines including CI/CD automation, model evaluation, monitoring, guardrails, observability, and performance benchmarking.• Optimize AI workloads using containerization (Docker), Kubernetes, Infrastructure as Code (Terraform/CloudFormation), and DevOps best practices.• Drive cross-functional collaboration with product, engineering, and business stakeholders to translate strategic AI initiatives into production-ready solutions.• Provide technical leadership, architectural guidance, and GenAI strategy consulting for enterprise clients adopting LLM and Agentic AI capabilities.• Extensive experience building and deploying LLM-powered applications and Agentic Systems in production environments.• Expertise in Cloud Architecture, Distributed Systems, DevOps, and AI Platform Engineering.

Education

• Institute of Management Studies, Noida

  Master of Computer Applications - MCA, Computer Science