Srikanth Enugula

• Led the engineering and DevSecOps efforts behind a next-gen AI SaaS platform focused on confidential model training. The solution was built using PyTorch, TensorFlow, and OpenFL, and deployed across secure multi-cloud environments.
• Boosted CI/CD efficiency by cutting build times in half—migrated from Jenkins to GitHub Actions and rolled out parallel workflows, Docker caching, and change-based testing to accelerate delivery.
• Designed and deployed a Kubernetes-based confidential computing infrastructure leveraging Intel SGX and TDX, enabling secure, large-scale federated learning across trusted compute nodes.
• Strengthened software security by embedding tools like Trivy, Coverity and HashiCorp Vault into the CI/CD pipeline, enforcing policies that led to a 30% reduction in vulnerabilities and full EO 14028 compliance.
• Cut Azure cloud costs by 50% through automated cleanup routines, resource tagging, and a hybrid deployment model that dynamically balanced workloads across on-prem and cloud.
• Built a comprehensive observability stack (logs, metrics, and traces) using Prometheus, Grafana, and custom alerting, which helped detect issues early and improve uptime and system reliability.
• Managed and mentored globally distributed teams across engineering, DevSecOps, and infrastructure; ensured projects stayed aligned with business goals and delivery milestones.
• Actively collaborated with product, security, and platform teams to align efforts around architecture, compliance, and performance, streamlining end-to-end delivery.
• Delivered secure-by-default CI/CD templates and reusable Terraform-based IaC patterns, which were adopted across multiple business units at Intel to speed up platform rollout.

• Developed an internal AI-powered platform (patent pending) to replace third-party commercial tools, leading to over $1 million in annual savings. Took a practical, open-source-first approach to avoid vendor lock-in.
• Took the lead on modernizing Gap’s legacy inventory systems, moving them to a microservices-based architecture using Spring Cloud. This helped improve reliability to 99% uptime and enabled better monitoring through tools like Apigee, Kibana, Micrometer, and DynaTrace.
• Personally trained and onboarded 80+ engineers across global teams, helping them ramp up on the new platform and driving cross-team consistency.
• Hired and built development, test automation, and DevOps teams from the ground up, focusing on getting the right mix of technical depth and team chemistry.
• Spearheaded the company’s migration from legacy SCM tools to Git, guiding distributed teams through best practices and helping improve code management with modern branching workflows.
• Designed and rolled out an internal UI testing framework that supported dynamic execution via containers, automated XPath healing, and actionable reporting—solving long-standing flakiness and debugging issues.
• As a result, cut test case development time by 60% and brought down full test suite execution time from nearly a week to under two days using Jenkins-based CI/CD pipelines.

• Led the development of Big Data ingestion and analytics platform leveraging Kafka, Hadoop, and Spark, processing.
• Engineered robust CI/CD pipelines for these data and ML workflows, incorporating automated testing to significantly improve deployment frequency.
• Architected and deployed the underlying scalable and secure AWS infrastructure using Infrastructure as Code (e.g., Terraform), meticulously managing IAM policies.

• Established and led a global engineering team from inception, successfully launching a high-availability microservices platform on AWS for B2B social media campaign management used by Fortune 500 companies.
• Architected and deployed DC/OS (Mesosphere) infrastructure to host and efficiently manage Kubernetes clusters, optimizing resource utilization and simplifying cluster operations.
• Resolved 100% of key recurring platform issues via customer service collaboration, earning a customer satisfaction award.

• Involved in architecture, design and development of DemandTec multi-tier application and trouble shooting issues.
• Deployed a 25-node Hadoop cluster (IBM Big Insights/IBM Cloud) and engineered data ingestion workflows for enterprise analytics.
• Built automated test framework to validate data pipeline accuracy and reliability resulting in improving the quality of product by 60%.
• Managed globally distributed Scrum teams, championing Agile practices to boost team velocity and project outcomes.

• Engineered reusable code libraries for an internal Fed cash application, streamlining development and enhancing architectural consistency.
• Bolstered backend system security by implementing strong encryption standards and robust authorization mechanisms.
• Improved project decision-making by establishing clear stakeholder communication channels and reporting structures.

Designed and built a secure web-based payment processing application, enabling users to complete transactions efficiently while maintaining strict compliance with security standards.

• Implemented robust authentication and role-based authorization, reducing unauthorized access incidents by over 90%.
• Streamlined the end-to-end payment workflow, which resulted in a 30% improvement in processing time and enhanced user experience.