DevOps Engineer

Job Title : DevOps Engineer

Experience : 3+ Years

Location : Mumbai

Employment Type : Full-time

Job Overview :

We’re looking for an experienced DevOps Engineer to design, build, and manage Kubernetes-based deployments for a microservices data discovery platform.

The ideal candidate has strong hands-on expertise with Helm, Docker, CI/CD pipelines, and cloud networking — and can handle complex deployments across on-prem, cloud, and air-gapped environments.

Mandatory Skills :

✅ Helm, Kubernetes, Docker

✅ Jenkins, ArgoCD, GitOps

✅ Cloud Networking (VPCs, bare metal vs. VMs)

✅ Storage (MinIO, Ceph, NFS, S3/EBS)

✅ Air-gapped & multi-tenant deployments

Key Responsibilities :

• Build and customize Helm charts from scratch.
• Implement CI/CD pipelines using Jenkins, ArgoCD, GitOps.
• Manage containerized deployments across on-prem/cloud setups.
• Work on air-gapped and restricted environments.
• Optimize for scalability, monitoring, and security (Prometheus, Grafana, RBAC, HPA).

Senior DevOps Engineer

AWS Infrastructure, Kubernetes & Production Operations

📍 Mumbai (On-site) | Full-time | 5-8 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior DevOps Engineer for a dedicated client engagement building an AI platform that turns a written prompt into a working, deployed web application.

The platform runs entirely on our own Kubernetes on AWS in Mumbai: multiple clusters, self-hosted Kafka, PostgreSQL, Redis and a complete observability stack, with untrusted AI-generated code executing inside isolated sandboxes.

This role owns that infrastructure end to end.

The mandatory requirement is hands-on production ownership of self-managed Kubernetes and self-hosted stateful services.

This is not a managed-services role: almost nothing here is a click in a console, and there is no platform team above you to escalate to.

You will pair daily with the Tech Architect who owns the architecture, and you own its execution, which covers clusters, networking, pipelines, observability, isolation, and the monthly cloud bill as a number you can explain line by line.

The role carries a deliberate path into LLM infrastructure over the first year, and we are saying so up front because we want someone who wants that direction.

A typical week includes rehearsing a cluster upgrade in a lower environment, tracing an unexplained cost line to its source, tuning autoscaling so non-production shuts down cleanly overnight, and hardening the boundary that keeps AI-generated code away from everything else.

Responsibilities:

Kubernetes Platform Ownership

Own multiple EKS clusters separated by trust boundary, covering platform services, messaging, sandboxed build environments, and hosting for customers' published applications.

Node pools, taints and tolerations, resource requests versus limits, pod disruption budgets, and the scheduling decisions that determine whether a cluster is efficient or merely large.

Plan and execute version upgrades without customer-visible downtime.

Infrastructure as Code

Everything in Terraform, with no console changes that are not in code.

Build reusable cluster modules rather than copies.

Keep state and reality in sync, and treat drift as a defect.

CI/CD and Release Engineering

Own the GitHub Actions pipelines and self-hosted runners: OIDC-based AWS authentication with no stored credentials, image builds, and rollouts across development, QA and UAT.

Move manifest templating from scripted substitution to Kustomize or Helm.

Make a rollback as routine as a deploy.

Network Architecture and Workload Isolation

VPC and subnet design, ingress through load balancers and service mesh, and eBPF-based network policy.

The platform runs code we did not write, so the isolation boundary is a primary deliverable: default-deny egress, kernel-level sandboxing for untrusted workloads, no platform credentials inside tenant pods, and one project per pod with nothing shared between customers.

Observability

Operate a self-hosted stack of Prometheus, Grafana, Loki, Tempo, OpenTelemetry and Alertmanager.

Build alerts engineers trust rather than mute.

Know what belongs in a metric, a log and a trace, and keep metric cardinality under control as tenant count grows.

Autoscaling and Capacity

Node autoscaling with Karpenter, and workload autoscaling on the signal that actually matters, which is queue depth or a schedule rather than CPU wherever CPU misleads.

Implement scale-to-zero across non-production and warm-pool patterns where cold starts are unacceptable.

Size capacity from measurement, not assumption.

Cost Operations

Own the cloud bill as an engineering artifact.

Attribute spend per cluster and per environment, right-size against real utilisation, apply Spot where interruption is safe and never where it is not, and investigate any line you cannot explain.

Instance family selection is a cost decision: match the family to the resource that binds first.

Self-Hosted Stateful Services

Operate Kafka, PostgreSQL and Redis in-cluster, covering persistence, replication, failover, upgrades, and backups you have actually restored from.

Rehearse the restore and record how long it took.

Security Posture

IAM and workload identity, migration away from static credentials, secret management, web application firewall rules, and closing the gaps you find.

Credential rotation and least privilege are ongoing work, not a one-time project.

AI Infrastructure (Growth Path)

Within the first year, take on the infrastructure serving AI workloads: multi-provider LLM gateway and routing, token and cost attribution, rate-limit-aware capacity planning, LLM tracing with Langfuse, vector databases such as pgvector and Qdrant, and self-hosted embedding models including GPU nodes on Kubernetes.

This is inference operations, not model training.

AI-Assisted Engineering Discipline

Use Claude, Cursor, and similar tools day to day for infrastructure code, scripts, and pipelines.

Set the team standard for safe use, review, and validation of AI-generated infrastructure before it ships.

Requirements:

Hands-on Production Ownership of Self-Managed Kubernetes (Mandatory)

Must have personally operated a production Kubernetes estate with operational responsibility including oncall, incident response, and upgrade ownership.

You understand why a cluster ends up over-provisioned and how to fix it.

Managed-platform-only experience, or Kubernetes limited to deploying into a cluster someone else runs, does not qualify.

5+ Years of Overall Engineering Experience

With at least 3 years in DevOps, SRE, or platform engineering.

This is not an ML science role.

A strong infrastructure background with genuine appetite for AI infrastructure is exactly the profile we want.

Proven Ability to Learn an Unfamiliar Technology to Production Depth

We are hiring for trajectory as much as for current tooling, so this carries real weight.

Be ready to walk us through something you picked up from scratch and then owned in production: what you got wrong in the first attempt, how you found out, and what you would do differently.

A candidate with a shorter tool list and a strong record of learning will be preferred over a longer list learned only at the surface.

Self-Hosted Stateful Services in Production

One or more of Kafka, PostgreSQL, Redis, or Elasticsearch operated by you, not by a managed service.

Backups, restores, failover, and version upgrades.

This matters more than any other line here, because almost everything we run, we run ourselves.

Infrastructure as Code Depth

Terraform in anger, including modules, state management, and recovering from drift.

Docker and image optimisation.

AWS at Depth

EKS, EC2, VPC, IAM, S3, RDS or Aurora, and load balancing.

You can read a bill and explain where the money went.

Networking Depth

VPC and subnet design, NAT and egress paths, load balancer behaviour, DNS, TLS, and Kubernetes networking.

Able to reason about address exhaustion and routing limits before they are hit rather than after.

Observability Depth

Production experience with Prometheus, Grafana, and a log or trace backend.

Comfortable instrumenting with OpenTelemetry.

Able to define alerts that are actionable and to resist the cardinality that makes a metrics system collapse.

CI/CD and Deployment Automation

Strong with GitHub Actions or GitLab CI, including self-hosted runners and short-lived cloud credentials.

Experience making deploys and rollbacks safe and routine.

Cost Management for Cloud Infrastructure

Demonstrated ownership of a cloud bill: right-sizing, reserved capacity or savings plans, Spot strategy, and tracing an anomaly to its cause.

Reliability Engineering

Comfortable defining SLOs and being accountable for them.

Experience with graceful shutdown, connection draining, disruption budgets, and long-lived connections such as WebSockets that autoscaling can otherwise sever.

Nice to Have:

• arm64 and Graviton estates
• eBPF networking with Cilium
• container runtime isolation such as gVisor, Kata, or Firecracker
• Kafka operations including partition and consumer-group management
• service mesh with Istio
• GPU workloads on Kubernetes
• hands-on familiarity with LLM observability tooling such as Langfuse or LangSmith
• India data-protection and residency requirements under the DPDP Act
• AWS certifications

• Minimum 3+ yrs of Experience in DevOps with AWS Platform
•     • Strong AWS knowledge and experience
•     • Experience in using CI/CD automation tools (Git, Jenkins, Configuration deployment tools ( Puppet/Chef/Ansible)
•     • Experience with IAC tools  Terraform
•     • Excellent experience in operating a container orchestration cluster (Kubernetes, Docker)
•     • Significant experience with Linux operating system environments
•     • Experience with infrastructure scripting solutions such as Python/Shell scripting
•     • Must have experience in designing Infrastructure automation framework.
•     • Good experience in any of the Setting up Monitoring tools and Dashboards ( Grafana/kafka)
•     • Excellent problem-solving, Log Analysis and troubleshooting skills
•     • Experience in setting up centralized logging for system (EKS, EC2) and application
•     • Process-oriented with great documentation skills
•     • Ability to work effectively within a team and with minimal supervision

About the opportunity:

This role is with Sporty Group. CareersInCloud shares this opportunity to help professionals discover relevant technology careers.

Hiring Company: Sporty Group

Sporty Group is looking for an experienced DevOps Engineer to join its remote engineering team.

This role involves managing AWS cloud infrastructure, Kubernetes environments, CI/CD pipelines, monitoring, automation, and improving system reliability.

Key Responsibilities:

• Manage AWS infrastructure and cloud operations

• Maintain Kubernetes clusters and Docker environments

• Build and improve CI/CD pipelines

• Monitor production systems using Grafana, Prometheus, and CloudWatch

• Troubleshoot Linux, networking, and infrastructure issues

Requirements:

• 3+ years of DevOps experience

• Strong AWS and Kubernetes experience

• Experience with Docker, Linux, CI/CD tools

• Good understanding of cloud infrastructure and automation

Apply here:

https://careersincloud.com/jobs/sporty-group-hiring-devops-engineer-remote-experienced

Job Responsibilities:

• Managing and maintaining the efficient functioning of containerized applications and systems within an organization
• Design, implement, and manage scalable Kubernetes clusters in cloud or on-premise environments
• Develop and maintain CI/CD pipelines to automate infrastructure and application deployments, and track all automation processes
• Implement workload automation using configuration management tools, as well as infrastructure as code (IaC) approaches for resource provisioning
• Monitor, troubleshoot, and optimize the performance of Kubernetes clusters and underlying cloud infrastructure
• Ensure high availability, security, and scalability of infrastructure through automation and best practices
• Establish and enforce cloud security standards, policies, and procedures Work agile technologies
• 
  

Primary Requirements:

• Kubernetes: Proven experience in managing Kubernetes clusters (min. 2-3 years)
• Linux/Unix: Proficiency in administering complex Linux infrastructures and services
• Infrastructure as Code: Hands-on experience with CM tools like Ansible, as well as the 
• knowledge of resource provisioning with Terraform or other Cloud-based utilities
• CI/CD Pipelines: Expertise in building and monitoring complex CI/CD pipelines to 
• manage the build, test, packaging, containerization and release processes of software
• Scripting & Automation: Strong scripting and process automation skills in Bash, Python
• Monitoring Tools: Experience with monitoring and logging tools (Prometheus, Grafana)
• Version Control: Proficient with Git and familiar with GitOps workflows.
• Security: Strong understanding of security best practices in cloud and containerized 
• environments.

Skills/Traits that would be an advantage:

• Kubernetes administration experience, including installation, configuration, and troubleshooting
• Kubernetes development experience
• Strong analytical and problem-solving skills
• Excellent communication and interpersonal skills
• Ability to work independently and as part of a team

Job Purpose and Impact

The DevOps Engineer is a key position to strengthen the security automation capabilities which have been identified as a critical area for growth and specialization within Global IT’s scope. As part of the Cyber Intelligence Operation’s DevOps Team, you will be helping shape our automation efforts by building, maintaining and supporting our security infrastructure.

Key Accountabilities

• Collaborate with internal and external partners to understand and evaluate business requirements.
• Implement modern engineering practices to ensure product quality.
• Provide designs, prototypes and implementations incorporating software engineering best practices, tools and monitoring according to industry standards.
• Write well-designed, testable and efficient code using full-stack engineering capability.
• Integrate software components into a fully functional software system.
• Independently solve moderately complex issues with minimal supervision, while escalating more complex issues to appropriate staff.
• Proficiency in at least one configuration management or orchestration tool, such as Ansible.
• Experience with cloud monitoring and logging services.

Qualifications

Minimum Qualifications

• Bachelor's degree in a related field or equivalent exp
• Knowledge of public cloud services & application programming interfaces
• Working exp with continuous integration and delivery practices

Preferred Qualifications

• 3-5 years of relevant exp whether in IT, IS, or software development
• Exp in:
•  Code repositories such as Git
• Scripting languages (Python & PowerShell)
• Using Windows, Linux, Unix, and mobile platforms within cloud services such as AWS
• Cloud infrastructure as a service (IaaS) / platform as a service (PaaS), microservices, Docker containers, Kubernetes, Terraform, Jenkins
• Databases such as Postgres, SQL, Elastic

This company is a network of the world's best developers - full-time, long-term remote software jobs with better compensation and career growth.  We enable our clients to accelerate their Cloud Offering, and Capitalize on Cloud.  We have our own IOT/AI platform and we provide professional services on that platform to build custom clouds for their IOT devices.  We also build mobile apps, run 24x7 devops/site reliability engineering for our clients.

We are looking for very hands-on SRE (Site Reliability Engineering) engineers with 3 to 6 years of experience. The person will be part of team that is responsible for designing & implementing automation from scratch for medium to large scale cloud infrastructure and providing 24x7 services to our North American / European customers. This also includes ensuring ~100% uptime for almost 50+ internal sites. The person is expected to deliver with both high speed and high quality as well as work for 40 Hours per week (~6.5 hours per day, 6 days per week) in shifts which will rotate every month.

This person MUST have:

• B.E Computer Science or equivalent
• 2+ Years of hands-on experience troubleshooting/setting up of the Linux environment, who can write shell scripts for any given requirement.
• 1+ Years of hands-on experience setting up/configuring AWS or GCP services from SCRATCH and maintaining them.
• 1+ Years of hands-on experience setting up/configuring Kubernetes & EKS and ensuring high availability of container orchestration.
• 1+ Years of hands-on experience setting up CICD from SCRATCH in Jenkins & Gitlab.
• Experience configuring/maintaining one monitoring tool.
• Excellent verbal & written communication skills.
• Candidates with certifications - AWS, GCP, CKA, etc will be preferred
• Hands-on experience with databases (Cassandra, MongoDB, MySQL, RDS).

Experience:

• Min 3 years of experience as SRE automation engineer building, running, and maintaining production sites. Not looking for candidates who have experience only as L1/L2 or Build & Deploy..

Location:

• Remotely, anywhere in India

Timings:

• The person is expected to deliver with both high speed and high quality as well as work for 40 Hours per week (~6.5 hours per day, 6 days per week) in shifts which will rotate every month.

Position:

• Full time/Direct
• We have great benefits such as PF, medical insurance, 12 annual company holidays, 12 PTO leaves per year, annual increments, Diwali bonus, spot bonuses and other incentives etc.
• We dont believe in locking in people with large notice periods.  You will stay here because you love the company.  We have only a 15 days notice period.

Striim (pronounced “stream” with two i’s for integration and intelligence) was founded in 2012 with a simple goal of helping companies make data useful the instant it’s born.

Striim’s enterprise-grade, streaming integration with intelligence platform makes it easy to build continuous, streaming data pipelines – including change data capture (CDC) – to power real-time cloud integration, log correlation, edge processing, and streaming analytics

2 - 5 Years of Experience in any Programming any language (Polyglot Preferred ) & System Operations • Awareness of Devops & Agile Methodologies • Proficient in leveraging CI and CD tools to automate testing and deployment . • Experience in working in an agile and fast paced environment . • Hands on knowledge of at least one cloud platform (AWS / GCP / Azure). • Cloud networking knowledge: should understand VPC, NATs, and routers. • Contributions to open source is a plus. • Good written communication skills are a must. Contributions to technical blogs / whitepapers will be an added advantage.

• As a DevOps Engineer, you need to have strong experience in CI/CD pipelines.
• Setup development, testing, automation tools, and IT infrastructure
• Defining and setting development, test, release, update, and support processes for DevOps operation
• Selecting and deploying appropriate CI/CD tools
• Deploy and maintain CI/CD pipelines across multiple environments (Mobile, Web API’s & AIML)

• 3+ years of experience as DevOps Engineer and strong working knowledge in CI/CD pipelines
• Experience administering and deploying development CI/CD using Git, BitBucket, CodeCommit, Jira, Jenkins, Maven, Gradle, etc
• Strong knowledge in Linux-based infrastructures and AWS/Azure/GCP environment
• Working knowledge on AWS (IAM, EC2, VPC, ELB, ALB, Autoscaling, Lambda, etc)
• Experience with Docker containerization and clustering (Kubernetes/ECS)
• Experience on Android source(AOSP) clone, build, and automation ecosystems
• Knowledge of scripting languages such as Python, Shell, Groovy, Bash, etc
• Familiar with Android ROM development and build process
• Knowledge of Agile Software Development methodologies