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