---
title: "Utkarsh Babbar - Member of Technical Staff (SDE2) in Hyderabad | Tal"
description: "Meet Utkarsh Babbar, MTS @Salesforce | DevOps | Infra as Code | Kubernetes | Python | Platform Engineering | Release Engineering based in Hyderabad. AI stack includes antigravity, opencode, and claudecode."
image: "https://tal.club/meet/utkarsh-babbar/share-image"
---

# Utkarsh Babbar on Tal

## Headline

MTS @Salesforce \| DevOps \| Infra as Code \| Kubernetes \| Python \| Platform Engineering \| Release Engineering

## About

I am a DevOps and Platform Engineer focused on automating infrastructure, scaling distributed systems, and building robust developer tooling across multi\-cloud environments\. 🔹 What I Do: Infrastructure as Code \(IaC\): Architect and provision scalable, multi\-region cloud environments using Terraform, Ansible, and Kubernetes\. Platform Automation: Build high\-throughput CI/CD pipelines and self\-service internal developer platforms to accelerate engineering velocity\. Backend Tooling: Develop resilient automation scripts and backend systems primarily in GoLang and Python\. AI Integration: Leverage AI native tools, LLMs, and MCP RAG architectures to build intelligent developer workflows and optimize infrastructure operations\. 🔹 Core Tech Stack: Cloud & Containers: AWS \(EKS, EC2, Lambda\), Azure, GCP, Kubernetes, Docker, Helm\. DevOps & Automation: Terraform, Ansible, CI/CD, Molecule, Groovy\. Languages & Frameworks: GoLang, Python, C\+\+, Java, Bash, Django\. AI & Observability: LLMs, MCP RAG, AI Native Tools, Prometheus, Grafana, Splunk, OpenTelemetry\. I thrive on eliminating operational toil and engineering scalable platforms that drive business success\. Let’s connect\! 📫 Reach out at: babbarutkarsh66@gmail\.com

## Location

Hyderabad

## AI stack

antigravity

opencode

claudecode

## Work experience

Member of Technical Staff \(SDE2\) at Salesforce, Dec 2024 \- Present · 1 yr 9 mos, • Designed asynchronous, high\-throughput cloud telemetries in Golang and Python, optimizing back\-end processing pipelines to scale reliably across production environments\. • Acted as primary system owner for scalable Splunk, Grafana, and Prometheus log pipelines, ingestion routing, and alerting rule topologies across enterprise clusters\. • Engineered real\-time telemetry dashboards based on strict SLAs, SLOs, and SLIs, reducing production mean time to detection \(MTTD\) by 30% for core infrastructure failures\. • Orchestrated high\-volume clustered nodes using Docker and AWS EKS \(Kubernetes\), developing clean Helm charts and custom ingress components to support massive transaction footprints\. • Evaluated data pipeline analytics to enforce cloud capacity guardrails, reducing runtime rollbacks by 10% and optimizing infrastructure cost efficiency\. • Led technical incident response rotations for high\-severity issues \(Sev 1/2\), establishing actionable root cause analysis \(RCA\) records and automated runbooks to minimize MTTR by 20%\.

Software Engineer 1 \(Cloud Engineering\) at Amadeus Labs, Jul 2022 \- Nov 2024 · 2 yrs 5 mos, Bengaluru, Karnataka, India, 🚀 Accelerated cloud deployment time using Terraform and Terragrunt IaC solutions\. 📜 Developed Ansible playbooks with Molecule tests for efficient infrastructure orchestration\. 🔄 Migrated over 10 applications to Kubernetes, optimizing host system usage and boosting team productivity with Helm charts\. 🐍 Created Python automation scripts, streamlining operational processes\. ✅ Ensured infrastructure code reliability by implementing Terraform unit tests in Golang with Terratest\.

SDE Intern at Amadeus Labs, Jan 2022 \- Jul 2022 · 7 mos, Karnataka, India, 🛠️ Crafted scalable Terraform deployments using Terragrunt and Ansible\. ⚙️ Managed Jenkins workflows with Groovy and automated 20\+ routine tasks with Python, reducing manual intervention and achieving high deployment accuracy\. 📊 Implemented monitoring and alerting solutions with Prometheus and Grafana, improving system visibility and reducing incident response times\.

Machine Learning Intern at Samsung Electronics, Jun 2021 \- Nov 2021 · 6 mos, India, 🔍 Explored and analyzed RNN algorithms, including LSTM and GRU, for image captioning on the Flickr dataset\. 🧹 Executed data cleansing using TensorFlow and scikit\-learn to ensure dataset quality\. 🤖 Engineered an ensemble of RNN models with Transformers, LSTM, GRU, and BiLSTM, achieving a CIDEr score of 0\.88 for enhanced image captioning\.

Subject Matter Expert\(CSE\) At Chegg\.inc at Chegg Inc\., Oct 2020 \- Nov 2021 · 1 yr 2 mos, India

## Education

B\.Tech, Electronics And Computer Science Engineering, Thapar Institute of Engineering & Technology

Doon Presidency School, Dehradun

[View the original profile](https://tal.club/meet/utkarsh-babbar)

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