Devops Engineer, Surveillance
Core
Design and build scalable data infrastructure, pipelines, and containerized platforms to power surveillance analytics, model development, and production deployment for compliance risk monitoring.
Role type
Senior DevOps/Platform Engineer (Data & ML Infrastructure)
Builds
Scalable data infrastructure, CI/CD pipelines, containerized orchestration layers, and observability stacks for surveillance analytics and ML workloads.
Domain
Financial services / Compliance surveillance / Cloud infrastructure
Deliverable
production ML models | infrastructure
Required skills
Cloud infrastructure design, Infrastructure as Code (Terraform), Container orchestration (Kubernetes), CI/CD automation, Observability stack management, Python scripting, Linux system administration, Data warehouse/lakehouse operations, AWS core services, GitOps principles.
Preferred skills
Experience with ML lifecycle automation tools (MLflow, Kubeflow, W&B), AWS SageMaker and Bedrock, Boto3, Cross-functional collaboration with data scientists and security teams.
Technologies
Terraform, Docker, Podman, Kubernetes, AWS EKS, ECS Fargate, GitHub Actions, MLflow, Kubeflow, Weights & Biases, Datadog, AWS CloudWatch, Grafana, Loki, Prometheus, Snowflake, Redshift, BigQuery, Databricks, AWS S3, EC2, Lambda, RDS, EMR, SageMaker, Bedrock, Boto3, Python, Bash.
Responsibilities
Lead design and build of scalable data infrastructure and pipelines; Build and operate infrastructure as code to provision and secure cloud resources; Design and maintain containerized platforms and orchestration layers; Develop and maintain CI/CD pipelines and ML lifecycle automation; Implement and evolve observability, logging, and alerting; Automate security controls and compliance checks within platform tooling; Optimize cloud cost, performance, and operational practices for large-scale workloads.
Seniority
Senior, hands-on IC