At a Glance
- Tasks: Design and maintain AI agents, ensuring security and scalability across platforms.
- Company: Join MUFG Investor Services, a leader in asset servicing with global reach.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Collaborate with top experts in a dynamic, innovative environment.
- Why this job: Be at the forefront of AI technology and make a real impact in finance.
- Qualifications: 5+ years in Platform Engineering/DevOps with strong coding skills.
The predicted salary is between 70000 - 90000 € per year.
MUFG Investor Services is a trusted partner to many of the world’s largest public and private funds, providing asset servicing and operational solutions built for alternatives. With over $1 trillion in client assets under administration, we offer fund administration, banking, payments, fund financing, foreign exchange overlay, corporate and regulatory services, custody, business consulting, and more. Operating from 17 locations worldwide, we help clients mitigate risk, enhance efficiency, and navigate the operational complexities of today’s investment management landscape.
We are seeking a highly skilled MLOps / Platform Engineer with a strong background in DevOps workflows and platform engineering best practices to join our AI initiative. This is a high-visibility project focused on deploying and managing AI agents across our infrastructure. You will work closely with the Research & Data Science team, backend and frontend engineers, and other technical teams to build a secure, scalable, and cost-optimized platform for AI workloads. This position supports AI Engineering and Data Science initiatives by focusing on infrastructure, operations, and platform reliability.
The Platform Engineer will work closely with AI Engineers and Data Scientists to ensure they have robust, scalable infrastructure to deploy their work.
Responsibilities:- Design, deploy, and maintain AI agents on Agent Core MCP servers and MCP gateways.
- Implement and manage observability using OpenTelemetry for logs and traces, integrating with Datadog.
- Ensure security, high availability, and cost optimization across all AI platform components.
- Provide infrastructure and deployment support to AI researchers and engineering teams, enabling integration of cutting‑edge technologies into production.
- Perform load testing, token cost measurement, and optimize resource utilization.
- Facilitate external vulnerability assessments and ensure compliance with security best practices.
- Troubleshoot and resolve platform issues promptly to maintain operational stability.
- Contribute to DevOps workflows, CI/CD pipelines, and automation for AI deployments.
- Support evaluation of third‑party products related to hosting AI agents or enhancing project capabilities.
- Assist in external audits and maintain documentation for platform architecture and processes.
- Develop and execute automation scripts using the AWS Boto3 SDK to deploy, test, and validate AI platform components across multiple environments.
- Implement Infrastructure as Code (IaC) using Terraform to provision and manage cloud resources for AI workloads, ensuring consistency and scalability.
- 5+ Years of experience in Platform Engineering / DevOps practice.
- 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.
- Familiarity with OpenTelemetry, Datadog, and observability tooling.
- Solid coding skills in languages commonly used for backend and automation (e.g., Python, Node.js, Go).
- Knowledge of microservices, container orchestration (Kubernetes/EKS), and cloud‑native architectures.
- Extensive knowledge of security practices, cost optimization, and performance testing.
- Interest and familiarity with latest trends in MCPs (Model Context Protocol) and AI agent frameworks.
- Working with AI/ML platforms or deploying AI agents in production environments.
- Exposure to high‑scale distributed systems and cloud infrastructure.
- Experience in observability and monitoring for complex systems.
- AWS certifications.
High visibility within the organization. Opportunity to work with cutting‑edge AI technologies and collaborate with leading experts.
Senior MLOps Engineer in London employer: Mufg Investorservices
MUFG Investor Services is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration among talented professionals. With a strong focus on employee growth, you will have the opportunity to work with cutting-edge AI technologies while benefiting from the stability and resources of one of the world's largest financial institutions. Our inclusive culture encourages continuous learning and development, making it an ideal place for those seeking meaningful and rewarding careers in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Prepare for those interviews by practising common questions and scenarios related to MLOps and platform engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable and confident.
✨Tip Number 3
Showcase your skills! Create a portfolio or GitHub repository with projects that highlight your experience in DevOps workflows and AI deployments. This gives potential employers a tangible look at what you can do.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior MLOps Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior MLOps Engineer role. Highlight your experience in platform engineering and DevOps workflows, as well as any relevant projects you've worked on that align with our AI initiatives.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work to show how you’ve implemented observability tools like OpenTelemetry or managed AWS services effectively.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you're passionate about AI and how your background makes you a perfect fit for our team. Keep it concise but impactful!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Mufg Investorservices
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS services, OpenTelemetry, and Terraform. Brush up on your coding skills in Python or Node.js, as you might be asked to solve a problem on the spot.
✨Showcase Your DevOps Experience
Prepare to discuss your previous experience with DevOps workflows and platform engineering. Be ready to share specific examples of how you've implemented CI/CD pipelines or managed observability tools like Datadog in past projects.
✨Understand the Business Context
Since MUFG Investor Services operates in a complex financial landscape, it’s crucial to understand their business model. Familiarise yourself with asset servicing and operational solutions to demonstrate that you can align your technical skills with their strategic goals.
✨Ask Insightful Questions
Prepare thoughtful questions about the AI initiative and how the team collaborates with other departments. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values.
