Senior Platform Engineer - Enterprise AI

Boston Scientific • Arden Hills, MN

16d • $89,200 - $169,500 • Hybrid

About The Position

Boston Scientific is seeking a Senior Platform Engineer to lead the design, development, and implementation of secure, scalable Model Context Protocol (MCP) capabilities across enterprise AI and multi-cloud environments. The role will shape enterprise MCP architecture, security, governance, and integration standards so AI agents and large language models can securely connect to enterprise applications, data platforms, and services. The engineer will collaborate with AI Engineering, Enterprise Architecture, Cloud Platform, Cybersecurity, and cross-functional teams to accelerate responsible AI adoption.

This position follows a hybrid work model, requiring employees to work from the local office in Arden Hills, Minnesota, or Marlborough, Massachusetts, at least three days per week. Boston Scientific will not offer or take over sponsorship of an employment visa for this position at this time.

Requirements

• Bachelor's degree in computer science, software engineering, data engineering, information systems, or a related technical field, or equivalent practical experience.
• At least 5 years of experience in enterprise architecture, cloud engineering, platform engineering, or distributed systems.
• Experience designing and implementing large-scale hybrid and multi-cloud platforms.
• Strong understanding of Model Context Protocol (MCP), AI agents, LLMs, retrieval-augmented generation (RAG), and agentic AI architectures.
• Expertise in at least two cloud platforms: AWS and Microsoft Azure.
• Strong knowledge of enterprise APIs, microservices, distributed systems, and integration architecture.
• Experience with OAuth/OIDC, identity and access management (IAM), role-based and attribute-based access controls (RBAC/ABAC), and Zero Trust security.
• Proficiency with Kubernetes, containers, CI/CD, and infrastructure-as-code.
• Proven experience developing enterprise architecture standards, governance frameworks, and technology roadmaps.
• Strong communication and stakeholder management skills, including the ability to influence technical leadership.

Nice To Haves

• Proven experience designing enterprise generative AI or agent platforms.
• Hands-on experience with MCP clients, servers, gateways, or related AI integration technologies.
• Proven experience with API management, service mesh, and multi-cloud architectures.
• Familiarity with OpenTelemetry, Fiddler, or enterprise observability platforms.
• Knowledge of responsible AI, AI governance, and emerging agent security practices.

Responsibilities

• Lead enterprise MCP strategy, architecture, standards, and roadmaps across hybrid and multi-cloud environments.
• Design, build, and operate scalable MCP platforms that connect AI agents, enterprise APIs, applications, and data sources.
• Establish MCP gateway and control plane capabilities, including service discovery, authentication, authorization, routing, policy enforcement, and observability.
• Develop standardized deployment and integration patterns across AWS, Azure, Kubernetes, and enterprise platforms.
• Implement Zero Trust security, identity management, least-privilege access, and safeguards against emerging AI agent threats.
• Define secure AI agent integration patterns, including tool execution, identity propagation, and human-in-the-loop approvals.
• Establish MCP governance, service lifecycle, architecture certification, and operational reliability standards.
• Develop reusable frameworks, automated CI/CD pipelines, infrastructure-as-code, and self-service developer capabilities.
• Partner with enterprise architecture, cybersecurity, and engineering teams to drive platform adoption, scalability, and continuous improvement.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior