Headline

Backend Engineer (Ex-Oracle Cloud Infrastructure) | Java & Spring Boot Microservices | Distributed Systems | Kubernetes & Cloud | AI Agentic Workflows | Cloud & AI Infrastructure

About

Backend Engineer with 2.5+ years of experience building large-scale cloud infrastructure and distributed backend systems at Oracle Cloud Infrastructure (OCI). I work on microservices, cloud-native platforms, and AI Ops systems powering compute orchestration and operational automation. At OCI, I design and develop scalable backend services and REST APIs used for infrastructure administration and automation workflows. My work includes building Agentic AI-driven systems for self-healing and root-cause analysis, improving operational reliability across production environments. My core expertise includes: • Java, Spring Boot, Microservices architecture • Distributed systems and system design • Kubernetes, Docker, and cloud-native deployments • Event-driven systems using Kafka and Redis • Cloud platforms: OCI and AWS • Python & FastAPI for AI-enabled services I enjoy working on complex backend problems involving scalability, reliability, and platform engineering, and I’m particularly interested in infrastructure systems and AI-enabled backend architectures.

Location

Bengaluru

AI stack

claude code

codex

cursor

mcp

ollama

LlamaIndex

Work experience

Member of Technical Staff at Oracle, Jul 2023 - Oct 2025 · 2 y 3 mo, Bengaluru, Karnataka, India, Architected the backend microservice for OCI AI Ops using Java and Micronaut, deploying onto Oracle’s managed Kubernetes (OKE) with Helm charts and automated scaling for production reliability. Developed Java-based event processors for an agentic AI pipeline handling 500+ automated infrastructure tickets daily, consuming real-time canary alerts via a managed message queue. Implemented dynamic context injection for LLM inferencing (Llama 3.1 via OCI GenAI), mapping infrastructure alerts to domain-specific runbooks in Object Storage to generate automated mitigation steps. Developed an LLM-based automated QA workflow to evaluate resolved support ticket quality, curating a high-quality dataset to predict resolutions for novel issues. Engineered a batched-parallel compute API automating fleet-wide health checks and repair calls to hypervisors, reducing server rack maintenance time by 70%. Built Python production canaries with Pydantic data validation and Pytest suites. Containerized via Docker/OCIR with Terraform provisioning and telemetry-driven monitoring alarms.

Intern at Oracle, Jun 2022 - Jul 2022 · 2 mos, Cloud Capacity Management

Education

Bachelor of Technology, Electrical, Electronics and Communications Engineering, National Institute of Technology, Tiruchirappalli

Maharishi International Residential School

Public links

github: https://github.com/jnishwanth