Naveen Kumar Kasarla

Naveen Kumar Kasarla has built a nine-year career in cloud infrastructure and DevOps engineering defined by a consistent theme: turning complex, high-dependency enterprise platforms into systems that are more automated, more secure, and easier to operate at scale. Across global organizations, he has developed a record of contributions that go beyond routine operational support—establishing reusable engineering standards, building scalable automation frameworks, and introducing AI-assisted practices that reflect the direction of next-generation cloud operations.

At Autodesk (2022–present), Kasarla serves as a Senior Software Engineer in the Enterprise Systems and Application Engineering (ESAE) group, supporting and modernizing AWS infrastructure that underpins core enterprise integration platforms—systems used by thousands of engineers and business users and central to Autodesk’s internal digital ecosystem. His remit spans foundational services such as MuleSoft and SAGE as well as modern platforms including Faros AI and PDEMP—systems that require consistent reliability, secure perimeter controls, and high operational clarity because failures ripple broadly across internal stakeholders.

Kasarla’s approach has been to standardize automation and reduce the operational surface area where human error typically enters. He introduced automation-first architecture patterns using Terraform, the Serverless Framework, and event-driven design, reducing manual provisioning by 80% and establishing reusable standards that have been adopted across multiple teams. In parallel, he engineered centralized observability across CloudWatch, Dynatrace, and BigPanda—moving from reactive firefighting to proactive detection and automated correlation of anomalies. His security work has been equally outcome-oriented: he implemented AWS WAF protections that reduced security incidents by 40% and built automated certificate governance using ACM and CloudFront to achieve full encryption compliance and eliminate manual certificate management risk. Collectively, these efforts shaped internal engineering guidelines, influenced platform strategy, and delivered measurable improvements in reliability and security—impact that is typically associated with platform-level ownership rather than narrow task delivery.

Prior to Autodesk, Kasarla contributed to large-scale global cloud transformation at Nike (2016–2022) as a DevOps and AWS Cloud Engineer supporting the Product Creation Excellence (PCX) initiative. PCX unified product creation, manufacturing, and lifecycle data into a cloud platform operating at global supply chain scale, built on a multi-account AWS Landing Zone and Control Tower architecture. In this environment, success depends on cost control, deployment discipline, and consistent reliability across many workloads and teams. Kasarla designed and deployed serverless services using AWS Lambda, API Gateway, and DynamoDB, reducing operating costs by 30% while improving response times and scalability. He built CI/CD automation using Jenkins and GitHub Actions to support multi-environment deployments and helped establish this pipeline model as a standard across teams. His work also included authoring CloudFormation and Terraform modules, implementing monitoring with CloudWatch and New Relic, and building Python and Bash automation tools that eliminated manual operational burden—contributions that compound over time in large enterprises because they reduce friction for every subsequent release.

Beyond core platform engineering, Kasarla has also pushed into the emerging space where AI augments cloud operations. He developed modular architectures using MCP Server and incorporated AI-assisted engineering tooling—such as Cursor and LLM-based workflows—for automated code generation, configuration intelligence, and CI/CD optimization. The significance of this work lies in its intent: treating AI not as a feature bolted onto a product, but as an operational accelerator that reduces human error, improves configuration management, and increases engineering velocity across infrastructure lifecycle tasks.

Taken together, Kasarla’s profile reflects Fellow-level characteristics in the cloud and DevOps discipline: measurable outcomes, reusable standards adopted by multiple teams, and forward-looking innovation that modernizes not only the platforms themselves but also the way engineering organizations build and operate them.