Senior AI Platform Engineer

Our Global Diabetes Capability Center in Pune is expanding to serve more people living with diabetes globally. Our state-of-the-art facility is dedicated to transforming diabetes management through innovative solutions and technologies that reduce the burden of living with diabetes. Were a mission-driven leader in medical technology and solutions with a legacy of integrity and innovation, join our new Minimed India Hub as Senior AI Platform Engineer. We are seeking an experienced Senior AI Platform Engineer to join our team. This candidate will have a strong background in Platform Engineering practices, with extensive experience in designing and creating AI Platform.

Medtronic has announced its intention to separate the Diabetes division to promote future growth and innovation within the business and reallocate investments and resources across Medtronic, subject to applicable information and consultation requirements.

This separation provides our team with a bold opportunity to unleash our potential, enabling us to operate with greater speed and agility. As a separate entity, we anticipate leveraging increased investments to drive meaningful innovation and enhance our impact on patient

care.

Responsibilities may include the following and other duties may be assigned:

• Develop and maintain robust, scalable data pipelines and infrastructure automation workflows using GitHub, AWS, and Databricks.
• Implement and manage CI/CD pipelines using GitHub Actions and GitLab CI/CD for automated infrastructure deployment, testing, and validation.
• Deploy and manage Databricks LLM Runtime or custom Hugging Face models within Databricks notebooks and model serving endpoints.
• Integrate LangSmith for tracing, debugging, and evaluating LLM chains and agentic workflows, including setting up datasets for testing and monitoring production runs.
• Design and implement stateful agentic applications using LangGraph, including graph-based workflows for multi-actor agents with tool integrations, memory management, and human-inthe-loop controls.
• Configure and manage AI Gateways (e.g., Cloudflare AI Gateway or equivalent) to handle
• routing, caching, rate limiting, and security for agentic AI API calls, ensuring efficient interactions with external tools and LLMs.
• Manage and optimize Cloud Infrastructure costs, usage, and performance through tagging policies, right-sizing EC2 instances, storage tiering strategies, and auto-scaling.
• Set up infrastructure observability and performance dashboards using AWS CloudWatch for real-time insights into cloud resources and data pipelines.
• Establish agent-specific monitoring, such as detecting workflow bottlenecks, agent decision traces, or failure recovery in LangGraph/LangSmith-integrated systems.
• Develop and manage Terraform or CloudFormation modules to automate infrastructure provisioning across AWS accounts and environments.
• Implement and enforce cloud security policies, IAM roles, encryption mechanisms (KMS), and compliance configurations.
• Enforce security best practices for agentic platforms, including API key rotation in AI Gateways, prompt injection prevention, and access controls for agent-tool interactions.
• Administer Databricks Workspaces, clusters, access controls, and integrations with Cloud Storage and identity providers.
• Enforce DevSecOps practices for infrastructure-as-code, ensuring all changes are peerreviewed, tested, and compliant with internal security policies.
• Coordinate cloud software releases, patching schedules, and vulnerability remediations using Systems Manager Patch Manager.
• Automate deployment and scaling of agentic AI components, such as triggering LangGraph workflows via event-driven architectures or integrating with serverless functions.
• Perform incident response, disaster recovery planning, and post-mortem analysis for operational outages.
• Collaborate with cross-functional teams including Data Scientists, Data Engineers, and other stakeholders to gather and implement infrastructure and data requirements.
• Work with AI teams to define requirements for agentic platforms, such as integrating custom tools into LangGraph agents or optimizing gateway configurations for high-throughput agent queries