Senior DevOps Engineer - Remote

ClanX · India · posted 689mo ago

engineering devops machine-learning remote jobs in india

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About this role

DevOps Engineer with 3+ years of experience to build, automate, and operate scalable cloud infrastructure, CI/CD pipelines, and ML workloads across multi-cloud environments.

Company Details

Conqr AI is an early-stage startup building AI solutions for regulated, document-heavy professional workflows. The company focuses on privacy, security, reliability, and delivering high-impact AI products for enterprise users.

Website:

Requirements

3+ years of experience in DevOps, Cloud Infrastructure, or Site Reliability Engineering.
Hands-on experience with AWS, GCP, and/or Azure.
Strong knowledge of Docker and Kubernetes.
Experience building and managing CI/CD pipelines.
Proficiency with Infrastructure as Code tools such as Terraform.
Experience with Git, GitHub Actions, or similar automation tools.
Understanding of monitoring, logging, and observability platforms.
Experience managing production infrastructure with a focus on reliability and scalability.
Knowledge of networking, VPCs, security groups, and cloud-native services.
Familiarity with GPU infrastructure and ML workload deployment is a plus.
Strong troubleshooting and problem-solving skills.
Excellent written and verbal communication skills in English.

Responsibilities

Design, build, and operate infrastructure across AWS, GCP, and Azure.
Optimize cloud environments for performance, reliability, scalability, and cost efficiency.
Own CI/CD pipelines from code integration through automated deployment.
Implement and maintain Infrastructure as Code using Terraform or similar tools.
Containerize and orchestrate services using Docker and Kubernetes.
Manage GPU-enabled infrastructure for AI model training and inference workloads.
Build and maintain monitoring, logging, and alerting systems.
Support private, VPC-isolated enterprise deployments with strong security and audit capabilities.
Collaborate with ML teams to deploy and scale training and inference workloads.
Work closely with Security and Engineering teams to improve infrastructure resilience and operational excellence.
Maintain infrastructure documentation and operational best practices.