Systems Controller - DevOps Lead

• Closing date: 13-Sep-2025

JOB PURPOSE:
As a DevOps & MLOps Lead, you will be responsible for architecting and managing CI/CD pipelines, cloud infrastructure, and automation frameworks that enable efficient and reliable software delivery. In addition to creating, deploying & maintaining machine learning models for efficient & reliable delivery & enhancement of ML & AI technologies. Moreover, you will lead cross-functional collaboration, mentor engineers, and drive continuous improvement across the DevOps & MLOps lifecycle.

ACCOUNTABILITIES:

• Designing, implementing, and maintaining CI/CD pipelines for code deployment, test automation, code quality, and telemetry.
• Integrating code quality tools such as SonarQube and Repository managers like Sonatype nexus into CI/CD pipelines.
• Leading the optimization of build pipelines to enhance performance, scalability, and supportability.
• Managing container deployment and orchestration using Docker and Kubernetes.
• Overseeing cloud infrastructure across AWS, Azure, or GCP, ensuring reliability and scalability.
• Implementing monitoring, alerting, and log aggregation solutions to improve system observability.
• Collaborating on cloud migration strategies, virtualization, and performance tuning.
• Analyzing system data to solve complex problems and contribute to technical design decisions.
• Troubleshooting issues, resolving defects, and conducting independent testing.
• Mentoring junior engineers and fostering a culture of continuous learning and innovation.
• Applying Site Reliability Engineering (SRE) principles for availability, performance, and capacity planning
• Identifying areas that will benefit from ML & AI integration in the existing technology stack & applications as well as matching solutions to use cases.
• Data gathering, cleansing and processing, as well as continual maintenance and validation of data sources and model outputs.
• Manage ML & AI models lifecycle from deployment to support to enhancements.
• Deploy insight modules and logging to guide model enhancement and future development as well as monitoring the models in production.

QUALIFICATIONS, EXPERIENCE & SKILLS:

Qualifications and Experience:

• Bachelor's degree in computer science, Engineering, or a related field.
• 6–10 years of experience in DevOps, cloud infrastructure, and MLOps.
• Professional certification in DevOps, MLOps, Kubernetes Administration is preferred.
• Hands-on experience with hybrid cloud environments and cloud platforms like AWS, Azure, or GCP.
• Proficiency in CI/CD tools (e.g., Git, Jenkins, GitLab CI) and infrastructure automation (e.g., Terraform, Ansible).
• Deep expertise in Kubernetes, Docker, AWS, Azure, and GCP.
• Experience with monitoring and logging tools such as Grafana, ELK, and Splunk.
• Hands-on experience with provisioning and configuration management tools like Terraform and Ansible.
• Knowledge of OWASP security best practices, ISO 27001 and ISO 20000 standards.
• Expertise in container orchestration (Kubernetes/OpenShift) and Linux system administration.
• Strong scripting skills in Shell, Python, or Go.
• Familiarity with microservices architecture and modern deployment practices.
• Expertise in ML tools (e.g. TensorFlow, PyTorch) and LLM frameworks (e.g. langchain)