AI DevOps & Cloud Engineer (MLOps)

About the role

MultiBank Group is looking for an AI DevOps & Cloud Engineer with strong MLOps capabilities to design and own the cloud infrastructure that will power its AI initiative. This foundational role will create the platform from the ground up, enable seamless CI/CD for data and ML teams, and evolve the environment into a production‑grade MLOps solution.

Key responsibilities

• Design, build and manage the full AWS infrastructure for AI workloads, covering compute, networking, storage, IAM and cost optimisation.
• Create and maintain CI/CD pipelines for data engineers, ML engineers and data scientists using GitHub Actions or GitLab CI, applying GitOps principles.
• Own Docker and Kubernetes environments for model training, batch processing and real‑time inference.
• Collaborate with ML engineers to deploy models, set up inference endpoints and batch scoring pipelines.
• Implement workflow orchestration with Airflow, Dagster or Prefect for scheduling and monitoring data/ML pipelines.
• Establish end‑to‑end observability, including alerts and dashboards for infrastructure, application performance and model health.
• Advance MLOps practices by adding drift detection, experiment tracking, data quality checks and automated retraining triggers.
• Integrate analytics platforms (Segment, Amplitude, Adjust, Firebase, MoEngage) into the central AWS data stack.
• Document infrastructure, deployment processes and operational runbooks while ensuring security and compliance.

Required profile

• 5‑10+ years of experience in DevOps, Cloud Engineering or Site Reliability Engineering.
• Proven track record of building cloud infrastructure from scratch, not just maintaining existing environments.
• Strong understanding of security, compliance and cost‑management in regulated financial services.

Required skills

• AWS (compute, networking, storage, IAM)
• Docker
• Kubernetes
• GitHub Actions or GitLab CI
• GitOps principles
• Airflow, Dagster or Prefect
• CI/CD pipeline design
• Model serving, inference endpoints, batch scoring
• Observability, monitoring and alerting tools
• Integration with Segment, Amplitude, Adjust, Firebase, MoEngage