P S Sree Harsha — Résumé

Bangalore

• Architected HPE OpsNexus, an enterprise operations intelligence mesh that unifies siloed operational systems into a knowledge graph and reasons across domains to predict downstream business impact. It ranked #1 in HPE's FOCUS AI Ideathon 2026 and was taken to final review before the FOCUS Group leadership panel.
• Engineered 7 production-grade AI systems and the distributed backend services beneath them within HPE's Emerging Technologies Team, automating complex enterprise engineering workflows and giving engineers their time back.
• Architected 8 Kubernetes-native microservices and 16 modular AI orchestration services for scalable AI platforms, powering intelligent incident classification, retrieval-augmented generation, and the generation of 450+ standardized documents.
• Developed AI-powered workflow automation with human-in-the-loop (HITL) decision support wired into enterprise systems, reducing manual operational effort by 42%.
• Designed MLOps pipelines for multiple models across hybrid-cloud environments, alongside sustainable automation that improved infrastructure visibility and eliminated 14 engineering hours of manual analysis every week.
• Modernized legacy enterprise applications by migrating 16 backend services and their databases to containerized, cloud-native architectures, standardizing deployment, observability and rollback across the platform estate.
• Partnered with software, cloud and platform engineering teams across 4+ business units to deliver HPE OneAI, applying modern software engineering, DevOps and cloud-native practices.
• Contributing to Agentic & Augmented AI orchestration that integrates adaptive learning and real-time feedback (RLHF) for self-optimizing systems.
• Ramped rapidly on Red Hat OpenShift, OpenStack and HPE Ezmeral to support key enterprise accounts, sustaining platform stability through routine health checks, fast issue resolution, and clear operational SOPs (recognized in HPE's Points Recognition program).
• Endorsed by the Director of HPE Managed Services, with the recommendation published in HPE's magazine.

Bangalore

• Engineered automation scripts and Ansible playbooks to streamline deployment pipelines and enhance infrastructure reliability across multi-cloud environments.
• Designed and tested cloud-native architectures with AWS, Azure, and HPE GreenLake, optimizing resource allocation and supporting scalable, elastic applications.
• Developed microservice packaging strategies with Docker and explored container orchestration using Kubernetes for modular application lifecycles.
• Configured secure Linux environments with RHEL system management, including ACL-based permissions, SELinux tuning, and network segmentation.

Bangalore

• Architected 12+ microservices powering a production B2B SaaS ERP platform used by 500+ healthcare organizations and companies, handling high-volume operational and KPI data pipelines.
• Directed an end-to-end MERN B2B SaaS product from scratch alongside the CEO, covering intelligence and analytics, the admin system and the ERP database, lifting customer satisfaction 70% and conversion 20%; the CSR feature delivered was recognized by a Government of India office.
• Championed over 750 CI/CD deployments with DevOps practices to maintain dependable product releases with strict deadlines and high-quality service.
• Designed and launched 24 features achieving 45% faster response times and 3x user engagement, secured with JWT token-auth sessions; developed real-time dashboards and sales trackers for data-driven decisions.
• Improved API performance by 60% through query optimization, indexing strategies, and pagination refinement across MongoDB and relational datasets, cutting per-page latency 40%.
• Built a scalable admin portal with user management, analytics and tiered access for the subscription model, plus a user portal for market insights and real-time sales tracking used by healthcare centres.
• Led a cross-functional team through an Agile–DevOps model with daily scrum deployments; reduced bug reports by 50% through automated testing cycles, and the internship was extended from 3 to 15 months on performance.