Senior DevOps Engineer

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

We are Systematix and we are currently looking for a Senior DevOps Engineer - AI & Data Platform to help modernize and automate the engineering practices supporting a rapidly growing enterprise AI and Data ecosystem for one of our key clients.

ABOUT THE PROJECT

Our client is a global leader in science and technology, supporting a diverse portfolio of businesses across healthcare, life sciences, diagnostics, manufacturing and industrial innovation. As investment in AI, machine learning and advanced data capabilities continues to accelerate, the organization is modernizing the engineering practices and automation required to support these workloads at enterprise scale.
The primary objective is to eliminate manual infrastructure, build and deployment processes and replace them with automated, repeatable and reliable engineering pipelines. Working closely with Platform Engineering, MLOps and other technical teams, the successful candidate will help establish modern DevOps patterns and standards while remaining highly hands-on in their implementation.

ABOUT THE RESPONSIBILITIES

• Design, build and maintain CI/CD pipelines supporting cloud infrastructure, applications and AI/ML workloads.
• Implement Infrastructure as Code and automated Azure cloud provisioning.
• Create standardized and repeatable Development, UAT and Production deployment patterns.
• Automate application and infrastructure testing, validation, deployment and release processes.
• Develop reusable engineering tooling, templates and automation components.
• Integrate infrastructure and deployment automation with GitHub-based development workflows.
• Design and implement GitHub Actions or equivalent CI/CD workflows.
• Support containerized applications and workloads using Docker and Kubernetes.
• Partner with Platform Engineering teams to automate Azure infrastructure provisioning and deployment.
• Partner with MLOps engineers to automate machine learning lifecycle, deployment and operational processes.
• Build self-service capabilities that enable development, data science and machine learning teams to deploy and consume technology with minimal manual intervention.
• Identify manual engineering processes and replace them with scalable, code-driven automation.
• Improve deployment speed, consistency, repeatability, reliability and overall developer experience.
• Implement appropriate security, governance and operational controls within automated engineering processes.
• Help establish modern SDLC, DevOps, source control, deployment and engineering standards.
• Provide technical leadership and recommendations while remaining directly involved in engineering, coding, configuration and implementation.

ABOUT THE REQUIREMENTS

• Extensive senior-level DevOps engineering experience within complex enterprise environments.
• Strong hands-on experience with Microsoft Azure.
• Demonstrated expertise with Infrastructure as Code and automated cloud provisioning.
• Strong experience designing, building and maintaining enterprise CI/CD pipelines.
• Hands-on experience with GitHub, GitHub Actions or comparable Git-based CI/CD technologies.
• Strong experience with Docker, Kubernetes and containerized workloads.
• Advanced scripting and automation capabilities.
• Strong understanding of modern SDLC, source control, release management and deployment practices.
• Experience developing reusable automation, engineering templates, deployment patterns and tooling.
• Experience integrating infrastructure automation with application development and deployment workflows.
• Demonstrated experience transforming relatively manual or immature engineering environments into automated, repeatable and code-driven platforms.
• Strong troubleshooting and problem-solving capabilities.
• Ability to operate effectively as both a senior technical advisor and hands-on engineer.
• Strong communication and collaboration skills with the ability to work across DevOps, Platform Engineering, MLOps, cloud, security, data and application engineering teams.

PREFERRED QUALIFICATIONS

• Experience supporting infrastructure and deployment processes for AI and machine learning workloads.
• Experience with Azure Machine Learning and related Azure AI/data services.
• Experience working with MLOps engineering practices and machine learning deployment pipelines.
• Experience supporting GPU or accelerated computing environments.
• Strong Python development or scripting experience.
• Experience with Platform Engineering and internal developer platforms.
• Experience creating self-service engineering and deployment capabilities.
• Experience working within large, global or federated enterprise environments.
• Experience helping establish DevOps capabilities, standards and practices within an immature or evolving engineering environment.

ABOUT THE ROLE

This is a contract opportunity supporting a strategic enterprise AI, Data and Cloud engineering initiative.This is a senior, highly hands-on engineering role. The successful candidate will help define DevOps architecture, standards and engineering patterns while personally building and implementing the pipelines, automation and tooling required to put those standards into practice.

We are looking for an engineer who naturally approaches manual infrastructure and deployment processes as opportunities for automation and who is equally comfortable defining the solution and sitting down to build it.

AI DISCLOSURE

As part of our recruitment process, Systematix may use artificial intelligence (AI) tools to assist with resume screening, candidate matching and recruitment administration. All hiring decisions are ultimately made by our recruitment and hiring teams.

ABOUT SYSTEMATIX

Systematix is a Canadian-owned Global Consulting and Resourcing firm with nearly 50 years of experience delivering technology solutions to clients across North America and the United Kingdom. We provide the highest-caliber consulting solutions to a diverse client base across all levels of government and private industry. Systematix is committed to creating a diverse, inclusive environment and is proud to be an equal opportunity employer. At Systematix, we value diverse perspectives, experiences, and backgrounds.

Systematix. Solutions Focused. People Driven.