Senior Azure DevOps Engineer

We seek a skilled and motivated Azure DevOps engineer to join our dynamic team. The ideal candidate will design, implement, and manage CI/CD pipelines, automate deployments, and optimize cloud infrastructure using Azure DevOps tools and services. You will collaborate closely with development and IT teams to ensure seamless integration and delivery of software solutions in a fast-paced environment.

Responsibilities:

• Design, implement, and manage CI/CD pipelines using Azure DevOps.
• Automate infrastructure provisioning and deployments using Infrastructure as Code (IaC) tools like Terraform, ARM templates, or Azure CLI.
• Monitor and optimize Azure environments to ensure high availability, performance, and security.
• Collaborate with development, QA, and IT teams to streamline the software development lifecycle (SDLC).
• Troubleshoot and resolve issues related to build, deployment, and infrastructure.
• Implement and manage version control systems, primarily using Git.
• Manage containerization and orchestration using tools like Docker and Kubernetes.
• Ensure compliance with industry standards and best practices for security, scalability, and reliability.

Why this role exists

Our infrastructure footprint is growing faster than our headcount, and we believe most of that

gap should be closed by automation and AI agents — not by hiring more humans to do toil. We

need someone early in their career who treats manual work as a bug, ships scripts and agents

instead of tickets, and wants to grow into deeper ownership over the next two years.

You will not be the most senior person on the team. You will be the one who multiplies the team.

What you'll own

In your first 1 months

• Take ownership of one slice of our CI/CD pipeline and make it measurably

faster, more reliable, or cheaper. We expect a number on a dashboard to move.

• Build at least three internal automations that replace manual ops toil —

using AI agents (Claude Code, agentic CLIs, scripted LLM workflows) as your force

multiplier.

• Be the first responder for a defined set of alerts. Write the runbooks. Drive

the alert volume down.

• Support senior engineers on AI/ML infrastructure (GPU nodes, inference

services, model deployment) — observe, document, and gradually take on contained

changes under review.

By 3 months you should be

• The go-to person for at least two production systems.

• Shipping routine infrastructure changes without needing senior review.

• Treating "manual" as a code smell.

Required (we will reject without these)

• 0–3 years hands-on experience with one major cloud (AWS, GCP, or

Azure — one is fine, depth beats breadth).

• Fluent in Linux command line, bash, and at least one scripting language

(Python or Go preferred).

• Have shipped something to production that real users hit. A side project

counts; a graded coursework lab does not.

• Comfortable with Docker — you can explain what an image vs. a

container is and why it matters.

• Working knowledge of networking fundamentals: DNS, HTTP/HTTPS,

TLS, ports, basic subnets — enough to debug "it works on my machine."

• Git fluency: branches, merges, rebases, conflict resolution.

• CI/CD pipelines — you have authored or substantially modified pipelines

in GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar. Not just "I clicked Re-run."

• Kubernetes basics — kubectl for real work, can read pod logs,

understand deployments and services, can debug a CrashLoopBackOff without

panicking. You do not need to have run a cluster; you do need to have lived inside one.

• Active user of AI coding agents (Claude Code, Cursor, Copilot, agentic

CLIs, etc.). You should be able to walk us through specific tasks where they made you

faster, and specific tasks where they failed you and how you noticed. "I have tried it" is

not enough.

Bonus (real plus, not required)

• Infrastructure as Code: Terraform, Pulumi, or Ansible.

• Observability: Prometheus/Grafana, Datadog, OpenTelemetry, any APM.

• Have built or extended an LLM-based agent — a custom MCP server, a

scripted multi-step workflow, an internal tool that calls models in a loop. Anything beyond

chat-with-Claude.

• Exposure to GPU workloads, model serving (vLLM, Triton, TGI, etc.), or

ML pipelines.

What we don't care about

• Whether your degree is in CS — or whether you have a degree at all.

• Brand-name companies on your resume.

• Certifications. They are fine. They do not substitute for having shipped.

How we work

• We default to automation. If you do something manually twice, the third

time you script it or hand it to an agent.

• AI agents are part of the workflow, not a novelty. Expect interview

questions about exactly how you use them — and where you have caught them being

wrong.

• Small, reversible changes beat big-bang rollouts.

• Postmortems are blameless and written down.

• We push back on each other. If you only execute, you will be unhappy

here.

How to apply

Send:

• Your resume.

• A short note (≤200 words) describing one infra or automation problem you

solved, and how AI agents factored in — or did not, and why. We read these. Generic

notes get rejected.

Internal note — delete before posting externally

• Comp band, location policy, team name, and reporting line marked

[CONFIRM] need to be filled in before this goes external.

• The Required list is intentionally tight: CI/CD and Kubernetes basics

promoted from bonus. Expect this to filter ~80% of typical junior DevOps applicants. The

remaining pool will skew toward people who have actually shipped infra at a startup, not

bootcamp grads or pure cloud-cert holders.

• IaC, observability, agent-building, and GPU/ML serving stay as bonus.

Promoting any of these to required at 0–3 yrs collapses the pool to near-zero or forces

hiring senior people at junior comp. If you want IaC required, re-level this to mid (3–5

yrs) and raise the band.

• Screening implication: the resume screen should explicitly check for

CI/CD pipeline authorship and any K8s-touching production work. If neither is on the

resume, reject at screen. Do not waste interview slots.

• Pipeline watch: if fewer than ~15 qualified resumes after 2 weeks of

active sourcing, the first thing to relax is the AI-agent-fluency bar (move to bonus and

screen for it in interview instead). Do not relax the "shipped to production" requirement

— that is the load-bearing filter.

• Configure, optimize, document, and support of the infrastructure components of software products (which are hosted in collocated facilities and cloud services such as AWS)
• Design and build tools and frameworks that support deployment and management and platforms
• Design, build, and deliver cloud computing solutions, hosted services, and underlying software infrastructures
• Build core functionality of our cloud-based platform product, deliver secure, reliable services and construct third party integrations
• Assist in coaching application developers on proper DevOps techniques for building scalable applications in the microservices paradigm
• Foster collaboration with software product development and architecture teams to ensure releases are delivered with repeatable and auditable processes
• Support and troubleshoot scalability, high availability, performance, monitoring, backup, and restores of different environments
• Work independently across multiple platforms and applications to understand dependencies
• Evaluate new tools, technologies, and processes to improve speed, efficiency, and scalability of continuous integration environments
• Design and architect solutions for existing client-facing applications as they are moved into cloud environments such as AWS
• Competencies
• Full understanding of scripting and automated process management in languages such as Shell, Ruby and/ or Python
• Working Knowledge SCM tools such as Git, GitHub, Bitbucket, etc.
• Working knowledge of Amazon Web Services and related APIs
• Ability to deliver and manage web or cloud-based services
• General familiarity with monitoring tools
• General familiarity with configuration/provisioning tools such as Terraform
• Experience
• Experience working within an Agile type environment
• 4+ years of experience with cloud-based provisioning (Azure, AWS, Google), monitoring, troubleshooting, and related DevOps technologies
• 4+ years of experience with containerization/orchestration technologies like Rancher, Docker and Kubernetes

Role : Principal Devops Engineer

About the Client

It is a Product base company that has to build a platform using AI and ML technology for their transportation and logiticsThey also have a presence in the global market

Responsibilities and Requirements

• Experience in designing and maintaining high volume and scalable micro-services architecture on cloud infrastructure

• Knowledge in Linux/Unix Administration and Python/Shell Scripting

• Experience working with cloud platforms like AWS (EC2, ELB, S3, Auto-scaling, VPC, Lambda), GCP, Azure

• Knowledge in deployment automation, Continuous Integration and Continuous Deployment (Jenkins, Maven, Puppet, Chef, GitLab) and monitoring tools like Zabbix, Cloud Watch Monitoring, Nagios

• Knowledge of Java Virtual Machines, Apache Tomcat, Nginx, Apache Kafka, Microservices architecture, Caching mechanisms

• Experience in enterprise application development, maintenance and operations

• Knowledge of best practices and IT operations in an always-up, always-available service

• Excellent written and oral communication skills, judgment and decision-making skill

Skills:

• Strong working knowledge of AWS.
• Implements AWS cloud platform.
• Infrastructure as Code, GitLab CI/CD, and DevOps standard methodologies
• scripting in Shell, Python, Ruby or any preferred scripting language

Terraform expertise is a MUST for this role.

a short exercise on terraform to all shortlisted candidates to demonstrate their hands-on skills on terraform before rolling out the offer

Desired Profile

 Providing expertise on all matters related to CI, CD and DevOps.

 Building and maintaining highly available production systems.

 Developing and maintaining release related documents, such as release plan, release notes etc.

 Ensuring quality releases and managing release and configuration change conflicts to resolution.

 Tracking release and publishing release notes.  Investigating and resolving technical issues by deploying updates/ fixes.

 Onboard applications to DevOps process.

 Setup and configure build jobs.

 Create automated deployment scripts.

 Configure JIRA workflow, and integrate with Jenkins / Micro-services.

Qualification

 Degree/Diploma in Computer Science, Engineering or related field and have previous experience as a DevOps Engineer.

 AWS Certification will be a plus.

 Experience of automation and provisioning approaches, using tools such as Terraform & Cloud Formation

Skillset Required

 Solid experience within release management, infra architecture, CI&CD.

 Highly goal driven and work well in fast paced environments.

 Proven experience of using Jenkins, Unix Shell Commands, Container technology (Docker, Kubernetes),

Java Programming, Groovy Script, Git, Code Branching Strategy, Maven, Gradle, JIRA, ECS, OpenShift.

• Azure Devops - Working experience in Azure yaml pipelines. (Note – Some say they worked in yaml but it’s for Jenkins and not Azure devops)
• Azure – Infrastructure automation using Terraform/ARM templates. (Note – Some say that they worked in terraform but it’s for AWS and not Azure). Please confirm Terraform for Azure infrastructure automation.
• Powershell scripting to automate and deploy .Net applications.

Mandatory Requirement/ Preference:

1.PowerBuild technology experience with minimum 8+ years

1. Excellent command on ASP.NET, Angular5/6/7/any version, MVC, Sql Server.
2. Should have strong debugging skills on Developer Tools of the browser and Working with Cross Browser UI

4.Working knowledge of the Microsoft Windows Platform and Microsoft Office applications.

1. Detailed technical knowledge of Angular any version, C#.Net (Visual Studio) development tools.
2. Experience with DevExpress components desirable.
3. Experience with DATA along with DevOps and GitHub.
4. ANgularJS is different to Angular. AngularJS experience is not relevant to us