Senior DevOps / ML Infrastructure Engineer - AI Lab

Secure Global Money Transfers with Cutting-Edge Technology and join our mission to protect cross-border transactions, helping customers send money safely worldwide. As DevOps / ML Infrastructure Engineer in our AI Lab, you'll maintain and scale our infrastructure while enabling seamless ML model integration into production workflows. You'll work alongside our Senior MLOps Architect to build a comprehensive ML platform that serves multiple teams across the organization.What You'll Do:

• Manage multiple orchestration platforms: Kubernetes in AWS (CloudFormation) and on-prem Kubernetes clusters
• Maintain Apache Flink infrastructure (managed in AWS or self-hosted in on-prem Kubernetes)
• Handle production support, incident response, and on-call rotations
• Perform regular patching activities and security vulnerability remediation
• Support and maintain workflow engine infrastructure
• Improve observability by utilizing Prometheus, Grafana, Splunk, Slack alerts, etc.

MLOps & Platform Development:

• Collaborate with Senior MLOps Architect to build and maintain ML infrastructure
• Set up and configure MLflow for experiment tracking and model registry
• Build automated MLOps pipelines for model training, experimentation, and deployment (Champion-Challenger, shadow mode)
• Support feature calculation pipelines and ETL processes
• Enable model serving infrastructure for Python-based ML services

• 5+ years of professional experience in DevOps or infrastructure engineering
• Strong hands-on experience with AWS services (EKS, ECR, SQS, S3, Managed Kafka, Managed Prometheus)
• Deep experience with Kubernetes in production environments (multi-cluster management is a plus)
• Proficiency with infrastructure as code: AWS CloudFormation and CDK (AWS Cloud Development Kit)
• Experience with containerization (Docker) and container orchestration
• Knowledge of setting up and maintaining CI/CD pipelines (GitHub Actions, ArgoCD, Jenkins, etc.)
• Hands-on experience with observability tools: Prometheus, Grafana, Splunk
• Experience with production support, incident response, and on-call rotations
• Strong communication skills (English B2+)
• Ability to work collaboratively with cross-functional teams (MLOps engineers, data scientists, software engineers)

It would be a plus:

• Experience with Apache Flink, Kafka, or other stream processing frameworks
• Understanding of ML lifecycle: model training, evaluation, deployment patterns
• Experience with workflow engines or rule engines
• Knowledge of fraud prevention, fintech, or compliance domains
• Understanding of feature stores, ETL pipelines, and data engineering concepts

• Remote work flexibility - work from anywhere- B2B contract with competitive gross compensation in USD
• Top-tier hardware to support your productivity
• A challenging role in a team of skilled professionals with opportunity to grow into MLOps specialization
• Direct collaboration with Senior MLOps Architect to learn and contribute to ML platform development
• Continuous learning and career growth opportunities
• Coverage for professional development: training, seminars, and conferences
• Access to high-quality English lessons
• Impact: Your work will directly prevent fraud while enabling secure financial access globally

Why This Role: This position offers a unique opportunity to work at the intersection of traditional DevOps and MLOps.