Senior DevOps Engineer for AI & Data Platform (Azure CI/CD)

Systematix group; Maryland; On-site; USD 140,000 - 190,000; Full time

Job summary

Systematix is seeking a Senior DevOps Engineer for an AI & Data Platform project in a fast-growing enterprise setting. The role is highly hands-on and demands building scalable CI/CD pipelines, IaC and Azure automation to support AI/ML workloads.

You will collaborate across Platform Engineering, MLOps and data teams, implement GitHub Actions, Docker and Kubernetes deployments, and drive standardized SDLC practices with strong engineering leadership.

Qualifications

• Extensive senior-level DevOps experience in complex environments.
• Hands-on Azure cloud, IaC and automated provisioning.
• Proven ability to design and maintain enterprise CI/CD pipelines.
• Experience with GitHub, GitHub Actions or equivalent CI/CD tools.
• Strong Docker, Kubernetes and containerized workloads.

Responsibilities

• Design, build and maintain CI/CD pipelines for cloud, apps and AI workloads.
• Implement Infrastructure as Code and automated Azure provisioning.
• Create standardized deployment patterns for Dev, UAT and Prod.
• Automate testing, validation, deployment and release processes.
• Develop tooling and templates for automation and self-service platforms.
• Integrate automation with GitHub-based workflows and actions.
• Support Docker/Kubernetes deployments and operator patterns.
• Collaborate with Platform Engineering, MLOps and security teams.
• Lead and mentor while contributing hands-on engineering work.

Skills

DevOps engineering

Azure

CI/CD pipelines

GitHub Actions

Docker

Kubernetes

Scripting

SDLC / Release management

Collaboration

Tools

GitHub

GitHub Actions

Azure

Docker

Kubernetes

Job description

Systematix is seeking a Senior DevOps Engineer for an AI & Data Platform project in a fast-growing enterprise setting. The role is highly hands-on and demands building scalable CI/CD pipelines, IaC and Azure automation to support AI/ML workloads.

You will collaborate across Platform Engineering, MLOps and data teams, implement GitHub Actions, Docker and Kubernetes deployments, and drive standardized SDLC practices with strong engineering leadership.