We are Systematix and we are currently looking for a Senior Cloud Platform Engineer – AI & Data to help design and build the foundational cloud platform supporting enterprise AI, machine learning, data science and scientific computing initiatives 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 building the cloud platform foundation required to support these workloads securely and at enterprise scale. The organization has significant existing Microsoft Azure capabilities; however, infrastructure provisioning and management remain too dependent on manual processes. The objective is to transition toward a modern Platform Engineering model built around Infrastructure as Code, automation, reusable architecture patterns and self-service capabilities. The successful candidate will initially operate as both architect and hands-on builder, helping establish the technical foundation and engineering practices that will ultimately support a broader enterprise platform engineering capability.
ABOUT THE RESPONSIBILITIES
Design and build scalable Microsoft Azure infrastructure supporting AI/ML, data science and scientific computing workloads.
Transform manually provisioned and managed cloud infrastructure into automated, reusable Infrastructure as Code.
Build automated infrastructure provisioning and deployment capabilities.
Establish repeatable Development, UAT and Production environment patterns.
Design and implement self-service platform capabilities that allow AI/ML, data and engineering teams to consume infrastructure without manual intervention.
Design and support GPU, accelerated computing and high-performance computing infrastructure.
Develop reusable architecture patterns capable of being adopted across multiple business units and operating companies.
Partner with MLOps, DevOps and Site Reliability Engineering teams to establish an integrated enterprise engineering platform.
Embed security, identity, governance, networking and operational requirements directly into reusable platform components and patterns.
Implement CI/CD and Git-based engineering practices for cloud infrastructure and platform development.
Improve developer experience by simplifying infrastructure consumption and significantly reducing provisioning timelines.
Evaluate existing cloud architecture and identify opportunities for automation, standardization and modernization.
Provide technical leadership and architectural direction while remaining highly hands-on with engineering and implementation.
Help establish platform engineering standards, practices, documentation and technical foundations that can be transitioned to a permanent internal engineering organization.
ABOUT THE REQUIREMENTS
Extensive hands-on Microsoft Azure cloud engineering experience within complex enterprise environments.
Strong Infrastructure as Code expertise using Terraform and/or equivalent Azure-native technologies.
Demonstrated experience designing and building reusable enterprise cloud platforms rather than primarily administering existing cloud environments.
Strong cloud architecture and Platform Engineering experience.
Hands-on experience with Kubernetes, containers and container orchestration.
Strong understanding of Azure networking, compute, storage, identity and security services.
Experience designing automated infrastructure provisioning and deployment capabilities.
Experience building reusable infrastructure components, templates, modules and standardized cloud patterns.
Demonstrated experience creating self-service infrastructure or developer platform capabilities.
Strong experience with CI/CD pipelines and Git-based engineering practices.
Strong automation and scripting capabilities.
Experience integrating security, governance and operational controls into cloud platform architecture.
Ability to operate effectively as both a senior technical architect and hands-on engineer.
Demonstrated ability to take ambiguous requirements and translate them into scalable technical solutions.
Strong communication and collaboration skills with the ability to work across infrastructure, cloud, security, DevOps, SRE, data and application engineering teams.
Experience with Azure Machine Learning and related Azure AI/data services.
Experience designing and supporting GPU and accelerated computing environments.
Experience with high-performance computing or scientific computing workloads.
Experience partnering with MLOps teams and supporting machine learning engineering platforms.
Experience working within large, global or federated enterprise environments.
Experience establishing a Platform Engineering capability within an immature, evolving or greenfield cloud environment.
Experience developing reusable cloud architecture patterns intended for adoption across multiple business units or organizations.
Experience improving developer experience through internal developer platforms, self-service infrastructure and automated provisioning.
ABOUT THE ROLE This is a contract opportunity supporting a strategic enterprise AI, data and cloud platform engineering initiative.
This is a senior, highly hands-on engineering position. The successful candidate will serve as one of the foundational members of an evolving Platform Engineering capability and will be expected to both define architecture and personally build the underlying platform components.
We are looking for a platform builder rather than a traditional Azure administrator: someone who has previously entered an immature cloud environment and helped transform it into a standardized, automated and code-driven engineering platform.
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.
APPLY NOW If you are interested in finding out more, please contact us or submit your resume to jobs@systematix.com.
Know someone who would be a great fit? We welcome referrals of qualified candidates and are always interested in connecting with talented technology professionals.
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.
Senior DevOps Engineer
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.
APPLY NOW If you are interested in finding out more, please contact us or submit your resume to jobs@systematix.com.
Know someone who would be a great fit? We welcome referrals of qualified candidates and are always interested in connecting with talented technology professionals.
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.
