Headline

Site Reliability Engineer @ ZEISS | Azure | Kubernetes (AKS) | Terraform | Datadog | Cloud Infrastructure | Python

About

Site Reliability Engineer with experience designing and operating cloud infrastructure on Microsoft Azure, including Azure Kubernetes Service (AKS), Terraform-based infrastructure automation, and Datadog observability platforms. Currently working at ZEISS, where I build and maintain scalable infrastructure, automate operational workflows, and improve system reliability across production environments. Key areas I work on include: • Cloud infrastructure and platform reliability on Azure • Infrastructure as Code using Terraform • Kubernetes deployments on Azure Kubernetes Service (AKS) • Monitoring and observability using Datadog • Security platform deployments including Cortex XDR • Automation using Python and REST APIs I enjoy solving reliability problems, building automation tools, and improving infrastructure performance and observability. Always open to conversations around Site Reliability Engineering, Cloud Infrastructure, and DevOps platforms.

Location

Bengaluru

AI stack

claude code

codex

cursor

github copilot

n8n

Microsoft Copilot

Work experience

DevOps Engineer at ZEISS Group, Jul 2023 - Present · 3 yrs 2 mos, Bengaluru, Karnataka, India · Hybrid, • Deployed and maintained Cortex XDR infrastructure on AKS, supporting secure endpoint telemetry ingestion. • Provisioned Azure Data Landing Zones using Terraform, reducing environment setup time from ~2 hours to ~40 minutes. • Configured DLZ-to-DLZ VNet peering, improving cross-environment connectivity and reducing troubleshooting time by ~30%. • Built RBAC migration tool, reducing manual access configuration effort by ~60%. • Automated BlackDuck vulnerability reporting, reducing report generation time from ~30 minutes to <5 minutes. • Implemented Datadog monitoring dashboards and alerts, improving incident detection speed by ~35%. • Resolved production incidents and ITSM tickets, improving MTTR by ~30%.

SWE Intern (Data Platform) at ZEISS Group, Jan 2023 - Jun 2023 · 6 mos, Bengaluru, Karnataka, India · Hybrid

Computer vision intern at Cloudastructure, Inc., May 2022 - Aug 2022 · 4 mos, Remote

Deep learning Intern at Carnegie Mellon University, Aug 2021 - Apr 2022 · 9 mos, Remote, Worked on the Fast and High-throughput Analysis of cryo-Electron Tomograms revealing Visual Proteomics of SARS-Cov-2, providing one of the best parameter values for Saliency Detection on the tomograms via analysis. Preparation of the protein data banks to the MRC (electron tomography) file for the Template Matching.

Education

Bachelor of Technology - BTech, Electronics and Communications Engineering, IIIT-Naya Raipur

10+2, BSP Senior Secondary School, Sector-X, Bhilai