Senior MLOps Engineer
MUFG Investor Services2 months ago
London, United KingdomSenior
Responsibilities
- Design, deploy, and maintain AI agents on Agent Core MCP servers and MCP gateways.
- Build and manage observability for logs and traces using OpenTelemetry and Datadog.
- Ensure security, high availability, cost optimization, and operational stability across AI platform components.
- Provide infrastructure and deployment support to AI researchers, data scientists, and engineering teams.
- Perform load testing, token cost measurement, resource optimization, troubleshooting, and platform issue resolution.
- Contribute to DevOps workflows, CI/CD pipelines, and automation for AI deployments.
- Evaluate third-party products for hosting AI agents and enhancing project capabilities.
- Support vulnerability assessments, external audits, security compliance, and platform documentation.
- Develop automation scripts using the AWS Boto3 SDK to deploy, test, and validate components across environments.
- Implement Infrastructure as Code with Terraform to provision and manage cloud resources.
Requirements
- 5+ years of experience in platform engineering or DevOps.
- Deep understanding of DevOps principles, workflows, and best practices.
- Proven experience in platform engineering and full-stack development.
- Proficiency in API design and integration.
- Hands-on experience with AWS services and familiarity with OpenTelemetry, Datadog, and observability tooling.
- Strong coding skills in Python, Node.js, Go, or comparable backend and automation languages.
- Knowledge of microservices, Kubernetes/EKS, container orchestration, and cloud-native architectures.
- Extensive knowledge of security practices, cost optimization, and performance testing.
- Interest in MCPs and AI agent frameworks.
- Preferred: experience with AI/ML platforms or production AI-agent deployments, high-scale distributed systems, complex-system observability, and AWS certifications.
Benefits
- High-visibility project with opportunities to work on cutting-edge AI technologies and collaborate with leading experts.
- Collaborative environment involving AI Engineering, Data Science, backend, frontend, and other technical teams.