AWS Certified DevOps Engineer — Professional  ·  Bengaluru, open to remote

Infrastructure that runs AI in production, built and secured.

Senior DevOps / MLOps / AI Infrastructure Engineer with 7+ years of experience. I design, automate and secure the Kubernetes, GPU/LLM serving and CI/CD platforms behind machine-learning workloads — across AWS, GCP and Azure.

Working acrossKubernetesTerraformAWSGCPAzurevLLM
90% ↓
less manual effort through IaC & automation
70% faster
deployments via CI/CD & GitOps pipelines
25% ↓
cloud cost through right-sizing & FinOps

Selected work

AI infrastructure, cloud security and multi-cloud platforms.

Production-shaped work from client deliveries and freelance engagements — not tutorials.

AI Infrastructure · LLM

On-Prem LLM on DGX Blackwell (GB10)

Fine-tuned Qwen & Gemma for client domains, applied NVFP4 / Gemma4 quantization for constrained GPU memory, and served via Ollama & vLLM on an NVIDIA DGX Blackwell (GB10) production Kubernetes cluster.

Qwen / Gemma→quantize→vLLM
GB10NVFP4production
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Platform · Security

CCTV Visual Analytics — Airport

Containerized real-time CCTV analytics for a large airport: HAProxy fronting UI, REST API, Kafka and MongoDB, with DMZ segmentation and security-zone isolation.

HAProxy→Kafka→MongoDB
DMZ isolation
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MLOps · IaC

MLOps Platform on AWS EKS

Modular Terraform (VPC / IAM / EKS CPU+GPU) with Ansible hardening; MLflow, DVC, Prometheus, Grafana and ClickHouse, secured with HashiCorp Vault and RBAC.

TerraformEKSMLflowVault
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Cloud · Data

GCP Serverless Data Pipeline

Real-time IoT pipeline — GCS → Cloud Run → BigQuery — built with Terraform and GitHub Actions, cutting misconfigurations by 70% and manual effort by 90%.

GCS→Cloud Run→BigQuery
70% ↓ misconfig90% ↓ manual
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