[Hiring] Azure DevOps Engineer (AI / Agentic) ML Ops Engineer @In All Media

Role Description

You will join a high-impact engineering squad as a "DevOps Futurist" and strategic advisor for a major international initiative. Rather than just executing standard pipelines, this role is dedicated to pioneering the next generation of automation by integrating AI and LLMs directly into DevOps workflows. The core challenge revolves around reducing human toil, scaling infrastructure autonomously, and designing intelligent, self-healing cloud ecosystems. You will play a pivotal role in architectural evolution, shifting the paradigm from traditional infrastructure management to AI-driven, autonomous platform engineering.

Key Responsibilities

• Drive AI-Driven Automation: Design, implement, and experiment with cutting-edge workflows that apply AI/LLMs to automate complex DevOps operations, reducing human intervention and operational friction.
• Architect Scalable Cloud Infrastructure: Oversee and optimize robust infrastructure solutions within Azure, ensuring top-tier performance, security, and monitoring.
• Define CI/CD & IaC Strategy: Champion best-in-class Infrastructure as Code (IaC) and continuous integration/deployment strategies to enable seamless, reliable software delivery.
• Act as a Strategic Technical Advisor: Influence architectural decisions and system design without needing direct authority, fostering a strong culture of research and innovation.
• Enhance System Reliability & Observability: Participate in deep architectural reviews, code reviews, and system design sessions to ensure high availability and cost-efficiency.

Qualifications

• 7+ years of experience in DevOps, Cloud Engineering, or Infrastructure architecture.
• Deep Azure Expertise: Proven mastery of Azure services, specifically Azure Kubernetes Service (AKS), cloud networking, compute, and native monitoring tools.
• Advanced Infrastructure as Code (IaC): Deep hands-on experience using Terraform, Bicep, or ARM templates.
• Robust Automation & Scripting: Strong programming proficiency in Python, Bash, or PowerShell to build custom automation tooling.
• AI/LLM Integration: Genuine, practical experience applying Large Language Models (LLMs) or AI tools to optimize real-world DevOps workflows.
• CI/CD Mastery: Solid background managing enterprise pipelines with GitHub Actions or Jenkins.
• Mindset: A strong research and experimentation mindset with the ability to think abstractly and design systems for long-term scalability.
• Experience working effectively within Agile teams and 100% remote environments.
• Fluent English for daily communication.

Nice-to-Have Skills

• Practical experience with Agentic frameworks and building autonomous workflows.
• Hands-on familiarity with AIOps platforms (e.g., Datadog AI, Dynatrace, etc.).
• Deep, granular knowledge of Kubernetes scaling, advanced observability, and cloud cost optimization.
• Experience navigating multi-platform environments (Azure blended with AWS).
• Strong background in Platform Engineering or Site Reliability Engineering (SRE) principles.

Time Zone & Collaboration

The role requires close collaboration with teams aligned to EST (Eastern Standard Time). Flexibility to overlap a minimum of 5-6 hours with North American business hours is expected.

Language

All interviews, technical documentation, and daily team communication will be conducted entirely in English.