
Cloud and Backend Engineer with nearly 8 years of experience at TCS, specializing in Enterprise Private Cloud platforms, OpenStack, and cloud-native backend development. Strong expertise in Python, Fast API, and REST API design, with proven experience building scalable Backend-For-Frontend (BFF) platforms for production systems. Demonstrated capability in multi-cloud environments (Azure, GCP), Cisco ACI integrations, CI/CD automation, and production operations. Hands-on experience working on GPU-enabled AI platforms for AI model deployment and developer environments. Known for delivery ownership, system reliability, and continuous upskilling.
Key Responsibilities & Contributions
Cloud & OpenStack Engineering
• Extensive hands-on experience with OpenStack services: Nova, Neutron, Cinder, Glance, Manila, Heat, Magnum, Keystone.
• Designed and implemented Fast API-based BFF APIs to abstract OpenStack SDKs for UI and automation consumers.
• Managed end-to-end cloud administration including VM lifecycle, volumes, images, networks, quotas, and issue troubleshooting.
Backend Development
• Developed secure, scalable REST APIs using Python and Fast API with strong validation, structured error handling, and consistent responses.
• Implemented multi-tenant access control using scoped tokens and project-level isolation.
• Built reusable service layers for compute, storage, networking, and backup workflows.
• Performed extensive API testing using Postman, curl, and automated validation approaches.
Networking & Integrations
• Integrated Cisco ACI (APIC) with OpenStack Neutron for automated network orchestration.
o VRF, Bridge Domain, EPG, L3Out configuration
o Tenant mapping and naming-convention alignment
• Worked on advanced Neutron constructs including ports, security groups, subnets, and allowed address pairs.
DevOps & Automation
• Implemented CI/CD pipelines using Jenkins across development, pre-production, and production environments.
• Deployed and tuned Fast API services using Uvicorn + Nginx with SSL and performance optimizations.
• Automated infrastructure provisioning using Terraform and AWX/Tower.
• Supported offline / air-gapped environments for images, providers, and deployment workflows.
Monitoring & Operations
• Integrated Prometheus and Grafana for monitoring, metrics, and observability.
• Developed automation scripts for log cleanup, disk monitoring, and alerting.
• Provided production support and root-cause analysis for critical issues
Key Projects
OpenStack Horizon BFF Platform
Role: Backend Engineer
• Built a centralized API layer replacing direct Horizon/OpenStack interactions.
• Improved security, performance, and maintainability by consolidating OpenStack logic.
• Implemented caching, pagination, quota summaries, and metadata enrichment.
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Network Portal – Cisco ACI & OpenStack
Role: Integration Engineer
• Developed APIs for Cisco ACI object creation and synchronization with OpenStack networking.
• Enabled tenant-based isolation and automated network provisioning.
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Cloud Reporting & Cost Management Portal
Role: Full Stack Developer (Initial Phase)
• Developed a Django-based portal for cloud usage reporting and cost tracking.
• Implemented role-based access control (Admin, Vendor, Internal Users).
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AI Studio – Unified AI Development & Alpha Cloud Provisioning Platform
Role: Backend & Platform Engineer
• Worked on AI Studio, a unified platform for AI model deployment, GPU-backed developer environments, and Alpha Cloud provisioning.
• Enabled one-click deployment of AI models (Hugging Face, LLaMA, custom models) and AI applications.
• Supported GPU-enabled developer environments including JupyterLab, Jupyter Notebook, and VSCode.
• Implemented backend APIs to auto-generate Kubernetes YAML for AI workloads based on user inputs.
• Integrated Alpha Cloud for automated VM and storage provisioning for AI workloads.
• Supported dynamic GPU slice allocation and GPU-aware scheduling for optimal resource utilization.
• Enabled namespace-based isolation to support secure multi-tenant AI environments.
• Integrated GitLab for version control of code, notebooks, and deployment configurations.
• Exposed real-time monitoring of GPU, CPU, RAM usage and slice allocation through dashboards.
• Supported lifecycle controls including auto-stop of idle AI workloads to optimize resource usage.