Open to AI infrastructure & cloud engineering roles

Swarup
Das

AI Infrastructure Engineer — cloud automation, reliable AI systems

I build the cloud foundations, delivery automation, observability, and agentic workflows that turn AI from an experiment into dependable production capability.

Get in touch ↗GitHub ↗LinkedIn ↗Résumé
Cloud & DevOps4+ years
AI operations MTTR−60%
Deployment uptime99.9%
Swarup Das, AI Infrastructure Engineer

01 / profile

Infrastructure is where AI earns trust.

I’m a Cloud & AI Infrastructure Engineer based in Bengaluru, focused on the practical systems that keep intelligent products secure, observable, and ready for reality.

I work across infrastructure as code, CI/CD, cloud security, Kubernetes, telemetry, and AI-assisted operations—because models matter, but deployment, guardrails, cost, and response matter too.

Focus
AI infrastructure · DevOps reliability
Based in
Bengaluru, India

02 / experience

Four years of making delivery dependable.

From RPA automation to enterprise cloud migrations and platform engineering—each role moved closer to the systems that keep teams shipping safely.

Jan 2026 – Present

stage: running

Bengaluru, KA

DevOps Engineer · Bridgestone Americas

Building the shared delivery platform and developer governance for a global enterprise, including the AI coding tools its engineers rely on.

  • Standardized CI/CD with reusable Azure DevOps YAML templates, cutting new pipeline creation time by 60% and pipeline code by 50%+.
  • Embedded SonarQube and Snyk in shared pipelines, with plan previews, approval gates, and policy checks for secure-by-default delivery.
  • Automated Azure DevOps access requests and repository creation through ServiceNow workflows, saving about 10 hours per week of manual effort.
  • Provisioned and managed Azure infrastructure with Terraform for 6 applications supporting the Bridgestone EMEA region.
  • Administer the enterprise Azure DevOps organization and GitHub Enterprise Cloud, publishing templates, documentation, and self-service workflows for consistent governance.
  • Run GitHub Copilot and Claude Code rollout: identity provider integration, RBAC, user lifecycle management, and license usage and cost tracking.

Azure DevOps · YAML Templates · Terraform · GitHub Enterprise · SonarQube · Snyk · ServiceNow

Aug 2023 – Dec 2025

stage: passed

Bengaluru, KA

DevOps Engineer · Cognizant

Led Azure migrations and landing-zone delivery for enterprise clients, in partnership with Microsoft.

  • Migrated enterprise workloads to Azure for Zee and Kantar (from AWS), M42 Healthcare (from Huawei Cloud), and Optum (UHG), improving cost and performance.
  • Designed and provisioned 20+ multi-environment Azure infrastructures using Landing Zone architecture, hub-and-spoke networking, management groups, policy guardrails, and modular Terraform with robust state management.
  • Built Azure DevOps and GitHub Actions pipelines for automated provisioning and application delivery, reducing deployment time by 70% and increasing release frequency.
  • Automated infrastructure validation and compliance checks with PowerShell and Azure Policy, eliminating 90% of manual verification.
  • Streamlined monitoring with Azure Monitor dashboards, alerts, and log analysis, cutting alert response time by 40%.
  • Partnered with development, security, networking, and operations teams on requirements, VNet/DNS/routing/load-balancer troubleshooting, and cost optimization. Earned a 5/5 performance rating in 2024.

Azure · Terraform · Landing Zones · Azure DevOps · GitHub Actions · PowerShell · Azure Policy · Azure Monitor

Jul 2022 – Jul 2023

stage: passed

Bengaluru, KA

Software Engineer · Tata Elxsi

Started in automation engineering, where I learned to turn repetitive operational work into reliable workflows.

  • Automated operational workflows with Python and UiPath, reducing manual work by 40% and saving 20 hours weekly.
  • Customized UiPath bots for client workflows, cutting processing time by 50% and improving operational efficiency by 60%.
  • Designed and deployed 4 intelligent bots and multiple POCs using UiPath Studio, Orchestrator, AI Center, and Document Understanding, using Azure for secure, scalable automation.

Python · UiPath · Orchestrator · AI Center · Document Understanding · Azure

03 / selected systems

Operational systems, built to be interrogated.

Each project connects a delivery or reliability problem to a working technical approach.

02 / delivery foundation

Azure Terraform Modules

A reusable Azure module library that encodes secure, repeatable standards for networking, compute, storage, and security services. Tested modules turn infrastructure requests into a predictable delivery path.

Terraform · Azure · Azure DevOps

Inspect repository ↗

03 / multi-cloud foundation

AWS Terraform Modules

A broad AWS module library covering core services from networking and compute to databases, containers, observability, and identity. Reusable Terraform building blocks make AWS infrastructure faster to compose and easier to standardize.

Terraform · AWS · HCL

Inspect repository ↗

04 / cost intelligence

Azure Cloud Cost Detective

An AI-powered cost investigation tool that scans Azure resource groups for over-provisioning, unused resources, and configuration issues, then delivers live analysis, actionable suggestions, and fix commands.

React · TypeScript · Python · FastAPI · OpenAI · PostgreSQL

Inspect repository ↗

05 / compliance automation

Azure Infrastructure Validation

PowerShell Pester validation for Azure configuration, policy, and continuous compliance. The automated checks reduced validation time by 98% while making configuration expectations visible and repeatable.

PowerShell · Pester · Azure · Terraform · Azure DevOps

Inspect repository ↗

06 / remediation intelligence

AI-Powered Azure Advisor Remediation

An AI agent that fetches Azure Advisor recommendations, grounds analysis in existing Terraform modules and environment configuration, and generates prioritized infrastructure improvements with before/after diffs, patches, and reviewable reports.

Python · Azure Advisor · Terraform · Streamlit

Inspect repository ↗

04 / systems index

The working surface.

AI runtime

Azure AI Foundry, LLMs, RAG, LangChain, FastAPI

Cloud foundation

Azure, AWS, GCP, Kubernetes, networking, identity

Delivery & policy

Terraform, GitHub Actions, Azure DevOps, Docker, Helm

Reliability loop

Prometheus, Grafana, ELK, OpenTelemetry, Pester

Engineering

Python, PowerShell, CI/CD, security automation

Practice

Incident response, architecture, cost awareness, governance

05 / credentials

Evidence beyond the repository.

01

Microsoft Azure certification

Verify the public credential record.

↗02

Cloud and infrastructure credentials

Supporting certifications and continued learning.

↗03

Complete résumé

Experience, education, and certification record.

↗

06 / contact

Let’s build something reliable.

Open to AI Infrastructure and Cloud/DevOps opportunities where automation and intelligent systems need to work together.

tech.swarupdas@gmail.comGitHub ↗LinkedIn ↗