DevOps Engineer – Agentic Engineering

Job Requirements

We are seeking a passionate and motivated DevOps Engineer with exposure to AI and Cloud Technologies to join our growing team.

This role is ideal for professionals with 1+ years of experience in DevOps, Cloud Infrastructure, Platform Engineering, or Site Reliability Engineering (SRE) who are looking to expand their expertise in AI infrastructure, automation, and cloud-native technologies.
The successful candidate will build agentic AI solutions on Azure that boost efficiency for our team and for the development teams using our cloud infrastructure and deployment tools.

You'll embed AI agents into our cloud runtime and CI/CD pipelines, with governance and human-in-the-loop oversight, to automate routine tasks and speed up provisioning and deployments.

Key Responsibilities

Agentic Engineering


* Identify AI use cases that boost efficiency and let us scale to more teams and partners without proportional effort.


* Pinpoint manual work that grows with every new team or partner, such as onboarding, provisioning, and support requests.


* Design and build AI agents for the selected use cases, from prototype to production.


* Embed agents into CI/CD pipelines, provisioning workflows, and the cloud runtime.


* Operate, monitor, and maintain agents in production.


* Enforce governance, guardrails, and human-in-the-loop approval for agent actions.


* Measure efficiency and scalability gains, and continuously improve agent quality, reliability, and cost.

Cloud Infrastructure & Platform Operations


* Design, deploy, and maintain cloud infrastructure on Azure or AWS.


* Operate Kubernetes and container platforms for application and AI workloads.


* Automate infrastructure provisioning with Infrastructure as Code (IaC).


* Build and maintain Helm charts for application deployments.


* Troubleshoot infrastructure, networking, and deployment issues.

DevOps & Automation


* Build and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or similar tools.


* Automate operational tasks with PowerShell and C#.


* Drive release management, deployment automation, and environment provisioning.


* Use AI-powered tools to increase operational efficiency.

AI & MLOps Support


* Deploy and monitor AI/ML applications and services.


* Maintain MLOps workflows with Azure ML, MLflow, or Kubeflow.


* Monitor performance of AI workloads and their infrastructure.

Monitoring & Reliability


* Implement monitoring and alerting with Prometheus, Grafana, ELK Stack, or cloud-native tools.


* Resolve incidents, run root cause analyses, and optimize performance.

Improve system reliability, scalability, and availability.

Required Technical Skills

Agentic Engineering


* Hands-on experience building AI agents with LLMs


* Familiarity with agent frameworks such as Semantic Kernel, AutoGen, or LangChain


* Experience integrating agents with tools, APIs, and knowledg...