Lead DevOps/MLOps Engineer

We are seeking a driven and highly skilled Lead DevOps/MLOps Engineer to assess client infrastructure to enable the deployment of Enterprise Data Platform (EDP) components, aiming to ensure seamless integration and operational efficiency for a leading oil and gas company. The focus is on evaluating existing systems and preparing them for a scalable data platform rollout.

Responsibilities

• Conduct comprehensive assessments of client infrastructure for EDP rollout feasibility
• Identify and document infrastructure gaps and recommend remediation actions
• Collaborate with data engineering and DevOps teams to align deployment strategies
• Develop and maintain deployment automation scripts and tools
• Coordinate with third-party vendors to ensure compatibility and support
• Monitor infrastructure performance and provide feedback for optimization
• Support continuous improvement of deployment processes and infrastructure standards
• Deploy platform and application workloads on Kubernetes

Requirements

• 5+ years of experience in DevOps practices tailored to data engineering environments
• Expertise in infrastructure assessment and readiness evaluation for data platform deployments
• Knowledge of EDP components and their deployment requirements
• Ability to analyze complex client environments and identify potential integration challenges
• Experience collaborating within cross-functional teams and coordinating with external vendors
• Proficiency in Docker, Kubernetes, and Linux
• Skills in CI/CD, Argo, and Python
• Understanding of machine learning and agentic AI applications, and what it takes to deploy and run them reliably in production
• English proficiency at B2 level or higher

Nice to have

• Background in MLflow and Airflow
• Knowledge of automated retraining tools
• Exposure to data quality and monitoring tools