DevOps Engineer — Kubernetes & Cloud

Platform & Infrastructure Engineering

Company: Eizen AI (Eigenmaps Private Limited)

Location: Bengaluru, India (On-site / Hybrid)

Experience: 3–5 years

Employment Type: Full-time

Function: Platform & Infrastructure Engineering

Reports To: Head of AI / Platform Lead

About Eizen AI

Eizen AI is an applied AI company building computer vision, video intelligence, and agentic AI systems for enterprises. We work with Fortune 500 organisations across manufacturing, retail, healthcare, and robotics, turning real-world video and operational data into decisions that run in production — not in slide decks.

Our platform stack includes eizenOS, our video intelligence platform for large-scale perception and analytics, and eizenX, our agentic workflow design layer for building and orchestrating AI agents. Alongside these, our proprietary Dual Vision System combines ego-vision and exo-vision to give robotic and industrial systems a far richer operational understanding of their environment than single-viewpoint approaches allow.

Eizen operates from Hyderabad — our primary R&D centre — with a growing presence in Bengaluru and Atlanta, USA. We are a research-led team: our work sits at the intersection of self-supervised learning for video, visual symbol grounding, and production-grade AI engineering. The company was founded and is led by a PhD in Cognitive Robotics from IIT Kanpur, and our engineering culture reflects that — deep technical ownership, first-principles problem solving, and an insistence that research ideas survive contact with production.

About This Role

Eizen is expanding its platform engineering team to support a major client engagement focused on building and scaling AI products. You will own the infrastructure these products run on — Kubernetes environments, CI/CD pipelines, cloud infrastructure, and production reliability — across development, staging, and production.

This is a hands-on Kubernetes and DevOps engineering role, not a coordination role. You will be the person who makes deployments predictable, environments reproducible, incidents short, and scaling boring. If you enjoy working close to real production systems — including AI/ML and GPU workloads — and want that work to visibly matter to enterprise customers, this role will suit you.

What You'll Do

• Manage and operate Kubernetes clusters across development, staging, and production environments.

• Deploy and manage containerised applications using Docker, Kubernetes, and Helm.

• Build and maintain CI/CD pipelines for automated build, test, deployment, and release workflows.

• Manage Kubernetes resources including Deployments, Services, Ingress, ConfigMaps, Secrets, Jobs, and autoscaling.

• Troubleshoot Kubernetes issues spanning pods, networking, resource utilisation, deployments, and application availability.

• Implement Infrastructure as Code using Terraform or equivalent tooling.

• Manage cloud infrastructure on AWS, Azure, or GCP.

• Configure application environments, secrets, access controls, and deployment configurations.

• Set up and maintain monitoring, logging, metrics, and alerting across applications and infrastructure.

• Improve infrastructure scalability, availability, security, and deployment reliability.

• Support production incidents, drive root-cause analysis, and resolve infrastructure issues.

• Partner closely with development and QA teams to improve deployment processes and production readiness.

• Implement cloud and Kubernetes security practices including RBAC, secrets management, network policies, and image security.

Must-Have Skills

• 3–5 years of experience in DevOps, Cloud, Platform, or Infrastructure Engineering.

• Strong hands-on experience running Kubernetes in production.

• Strong experience with Docker and containerised application deployments.

• Experience with Helm and Kubernetes configuration management.

• Experience building and maintaining CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.

• Hands-on experience with at least one major cloud platform — AWS, Azure, or GCP.

• Experience with Terraform or another Infrastructure as Code tool.

• Solid understanding of Linux, networking, DNS, load balancing, and HTTP/HTTPS.

• Practical experience with Kubernetes troubleshooting, deployments, scaling, and resource management.

• Experience with monitoring and logging tools such as Prometheus, Grafana, Datadog, or ELK.

• Good scripting skills in Bash or Python.

• Working understanding of production support, incident troubleshooting, and deployment best practices.

Nice to Have

• Experience with managed Kubernetes platforms — EKS, AKS, or GKE.

• Experience with Argo CD, Flux, or GitOps workflows.

• Knowledge of Kubernetes Ingress controllers, service networking, and autoscaling.

• Experience with Redis, PostgreSQL, Kafka, or comparable production infrastructure components.

• Familiarity with OpenTelemetry and distributed tracing.

• Exposure to AI/ML or GPU workloads on Kubernetes.

• Knowledge of cloud security, vulnerability scanning, and container security.

• Relevant Kubernetes or cloud certifications (CKA, CKAD, CKS, or cloud provider equivalents).

What Success Looks Like in the First Six Months

• Deployments across all environments are automated, repeatable, and low-drama.

• Infrastructure is defined as code, with environments reproducible from source.

• Monitoring and alerting give the team early warning rather than after-the-fact explanations.

• Mean time to recovery on production incidents is measurably shorter.

• Development and QA teams ship faster because the path to production is clearer.

Why Join Eizen

• Real production AI, at scale. Our systems process live video and run agentic workflows for Fortune 500 clients — the infrastructure challenges are genuine, not theoretical.

• Ownership from day one. Small, senior team. You will own systems end to end and your decisions will shape how we build.

• Technical depth. A research-led environment where AI/ML and GPU workloads are part of everyday infrastructure work.

• Global exposure. Work across our India and US operations with direct visibility into enterprise client engagements.

How to Apply

Send your CV, along with a short note on the most complex Kubernetes or production reliability problem you have solved, to careers@eizen.ai.

Fill up the form: https://forms.office.com/r/y9JFDDEZqX

Eizen AI is an equal opportunity employer. We evaluate applicants on capability and potential, and welcome candidates from all backgrounds.

Eizen

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DevOps Engineer — Kubernetes & Cloud