Senior Databricks AI Platform Engineer

Design and implement secure, scalable, and automated Databricks environments to support AI/ML workloads. Develop infrastructure-as-code (IaC) solutions using Terraform for provisioning Databricks, cloud resources, and network configurations. Build automation and self-service capabilities using Python, Java and APIs for platform onboarding, workspace provisioning, orchestration and monitoring. Collaborate with data science and ML teams to define compute requirements, governance policies, and efficient workflows across dev/qa/prod environments. Integrate Databricks offering with cloud-native services on Azure/AWS Champion CI/CD and GitOps for managing ML infrastructure and configurations. Ensure compliance with enterprise security and data governance policies using RBAC, Audit Controls, Encryption, Network Isolation, and policies. Monitor platform performance, reliability, and usage, and drive improvements to optimize cost and resource utilizations Proven experience with Terraform for building and managing infrastructure. Strong programming skills in Python and Java Hands-on experience with cloud networking, identity and access management, key vaults, monitoring, and logging in Azure Hands on experience with Databricks (Workspace management, Clusters, Jobs, MLFlow, Delta Lake, Unity Catalog, Mosaic AI) Deep understanding of Azure or AWS infrastructure (e.g. IAM, VNets/VPC, Storage, Networks, Compute, Key management, monitoring) Strong experience in distributed system design, development and deployment using agile/devops practices. Experience with CI/CD pipelines (GitHub Actions, or similar) Experience implementing monitoring and observability using Prometheus, Grafana or Databricks-native solutions. Good communication skills, excellent teamwork experience, ability to mentor and develop more junior developers, including participating in constructive code reviews 4+ Years. Bachelor's or master's degree in computer science, Engineering or a related field. Experience in multi-cloud environments (AWS/GCP) is a bonus Experience in working in highly regulated environments (finance, healthcare, etc.) is desirable Experience with Databricks REST APIs and SDKs Knowledge of MLFlow, Mosaic AC, & MLOps tooling Working with teams using Scrum, Kanban or other agile practices Proficiency with standard Linux command line and debugging tools Azure or AWS Certifications Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. If this role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks. Flexible work statement Interested in flexible working opportunities? Speak to our recruitment team to find out more. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.