Shivansh K. profile photo 1 on Tal

Shivansh K.

DevOps Engineer II @ Licious | Ex Lenskart | LLMOPS | GitOps

Greater Bengaluru Area

5+ years of work experience

Licious
Jul 20251 yr 2 mosPresent

Bengaluru

• Engineered an enterprise-grade SQL deployment automation framework using Jenkins, Bitbucket, AWS DynamoDB, and Secrets Manager — integrating SQLFluff linting, IAM-based authorization, and SlackOps alerting, achieving 88% faster deployment cycles and 95% reduction in human errors. • Provisioned a production-grade AWS EKS cluster with Cluster Autoscaler, KEDA, Redis, MySQL, and Kafka — fully automated via Terraform and Helm — enabling elastic, high-availability infrastructure for mission-critical workloads. • Migrated the entire Supply Chain microservices application to EKS with full observability stack (Prometheus, Grafana, EFK), achieving 99.9% uptime and a 40% improvement in resource utilization efficiency.
Lenskart.com
Feb 20223 yrs 5 mosJun 2025

Bengaluru

• Led end-to-end migration of 150+ microservices to AWS EKS, architecting a seamless transition that improved scalability, availability, and performance across four distinct Kubernetes cluster versions. • Architected a high-availability real-time monitoring and alerting framework using Prometheus and Blackbox Exporter — integrated with Google Chat webhooks via Alertmanager — reducing system downtime by 30% and improving service availability across all microservices. • Developed a multi-version compatible Helm Chart that enhanced operational efficiency by 30%, enabling consistent deployments across four Kubernetes cluster versions with minimal configuration drift. • Designed and optimized multi-architecture Dockerfiles using Buildx, multi-stage builds, and BuildKit caching — significantly reducing image sizes and build times across all microservices. • Implemented a customized EFK Stack (Elasticsearch, Fluentd, Kibana) for centralized log aggregation, enabling engineering teams to drastically reduce issue resolution turnaround time (TAT). • Architected an automated domain monitoring system for 400+ domains using GoDaddy APIs, Pushgateway, Prometheus, and Grafana — enabling real-time tracking, dynamic alerting, and proactive notification to prevent expiry incidents. • Built an end-to-end compliance pipeline integrating Lambda-based auto-tagging for EKS instances with real-time EC2 monitoring — enabling immediate detection and reporting of non-compliant resources via Google Chat. • Converted existing infrastructure to code using Terraformer, enabling version-controlled, auditable, and automated infrastructure management across the entire production environment.
LinuxWorld Informatics Pvt Ltd
Apr 20201 yrMar 2021

Jaipur, Rajasthan

• Designed and implemented end-to-end ML production systems, including project scoping, data processing, modeling strategies, and deployment requirements. • Established model baselines, addressed concept drift, and developed strategies for continuous improvement of production ML applications. Built data pipelines for gathering, cleaning, and validating datasets to ensure high-quality inputs for ML models. • Deployed and maintained ML models on Kubernetes, ensuring scalability, reliability, and efficient resource utilization. • Implemented saving and loading mechanisms for deep learning models using Keras for efficient model management. • Developed Computer Vision solutions leveraging Neural Networks for text data processing, image, and video analysis.
GitHub
@Shivansh5

Shivansh’s AI Stack

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Headline

DevOps Engineer II @ Licious | Ex Lenskart | LLMOPS | GitOps

About

I build infrastructure that doesn't break at 3am. Over the past 4+ years, I've designed and operated high-availability cloud platforms for two of India's fastest-growing consumer brands — Lenskart and Licious — serving millions of users across microservices-heavy, high-throughput environments. At Licious, I engineered a SQL deployment automation framework that cut deployment cycles by 88% and reduced human errors by 95%. I provisioned and migrated the entire Supply Chain microservices platform to AWS EKS — achieving 99.9% uptime with full observability (Prometheus + Grafana + EFK stack). At Lenskart, I led the migration of 150+ microservices to EKS, built a multi-version Helm chart system that improved operational efficiency by 30%, and architected a domain monitoring platform covering 400+ domains — all while reducing system downtime by 30%. What I bring to every team: → AWS: EKS, EC2, DynamoDB, Lambda, Secrets Manager, IAM, Kafka, Redis → Infrastructure as Code: Terraform, Helm, Ansible → Observability: Prometheus, Grafana, EFK Stack, New Relic, Alertmanager → CI/CD: Jenkins, GitLab CI, Bitbucket, Shell Scripting, Python → Kubernetes: Cluster Autoscaler, KEDA, multi-arch Docker, GitOps I care about reducing toil, improving reliability, and building systems that scale without drama. Currently open to Senior DevOps Engineer, Platform Engineer, or SRE roles in Bengaluru (open to Gurugram/remote)

Location

Greater Bengaluru Area

AI stack

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Work experience

DevOps Engineer II at Licious, Jul 2025 - Present · 1 yr 2 mos, Bengaluru, • Engineered an enterprise-grade SQL deployment automation framework using Jenkins, Bitbucket, AWS DynamoDB, and Secrets Manager — integrating SQLFluff linting, IAM-based authorization, and SlackOps alerting, achieving 88% faster deployment cycles and 95% reduction in human errors. • Provisioned a production-grade AWS EKS cluster with Cluster Autoscaler, KEDA, Redis, MySQL, and Kafka — fully automated via Terraform and Helm — enabling elastic, high-availability infrastructure for mission-critical workloads. • Migrated the entire Supply Chain microservices application to EKS with full observability stack (Prometheus, Grafana, EFK), achieving 99.9% uptime and a 40% improvement in resource utilization efficiency.

DevOps Engineer at Lenskart.com, Feb 2022 - Jun 2025 · 3 yrs 5 mos, Bengaluru, • Led end-to-end migration of 150+ microservices to AWS EKS, architecting a seamless transition that improved scalability, availability, and performance across four distinct Kubernetes cluster versions. • Architected a high-availability real-time monitoring and alerting framework using Prometheus and Blackbox Exporter — integrated with Google Chat webhooks via Alertmanager — reducing system downtime by 30% and improving service availability across all microservices. • Developed a multi-version compatible Helm Chart that enhanced operational efficiency by 30%, enabling consistent deployments across four Kubernetes cluster versions with minimal configuration drift. • Designed and optimized multi-architecture Dockerfiles using Buildx, multi-stage builds, and BuildKit caching — significantly reducing image sizes and build times across all microservices. • Implemented a customized EFK Stack (Elasticsearch, Fluentd, Kibana) for centralized log aggregation, enabling engineering teams to drastically reduce issue resolution turnaround time (TAT). • Architected an automated domain monitoring system for 400+ domains using GoDaddy APIs, Pushgateway, Prometheus, and Grafana — enabling real-time tracking, dynamic alerting, and proactive notification to prevent expiry incidents. • Built an end-to-end compliance pipeline integrating Lambda-based auto-tagging for EKS instances with real-time EC2 monitoring — enabling immediate detection and reporting of non-compliant resources via Google Chat. • Converted existing infrastructure to code using Terraformer, enabling version-controlled, auditable, and automated infrastructure management across the entire production environment.

MlOps at LinuxWorld Informatics Pvt Ltd, Apr 2020 - Mar 2021 · 1 yr, Jaipur, Rajasthan, • Designed and implemented end-to-end ML production systems, including project scoping, data processing, modeling strategies, and deployment requirements. • Established model baselines, addressed concept drift, and developed strategies for continuous improvement of production ML applications. Built data pipelines for gathering, cleaning, and validating datasets to ensure high-quality inputs for ML models. • Deployed and maintained ML models on Kubernetes, ensuring scalability, reliability, and efficient resource utilization. • Implemented saving and loading mechanisms for deep learning models using Keras for efficient model management. • Developed Computer Vision solutions leveraging Neural Networks for text data processing, image, and video analysis.

Public links

github: https://github.com/Shivansh5