Senior Platform Engineer - Enterprise AI

Boston Scientific•Arden Hills, MN

12h•$89,200 - $169,500•Hybrid

About The Position

Boston Scientific was recognized by Forbes as one of the Best Workplaces for Engineers in 2026, reflecting a culture where engineers do meaningful work. Boston Scientific was recognized as a Glassdoor Best Place to Work in 2026, ranking No. 15 on the Top 100 list, reflecting the culture our employees experience every day. We are 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. This role will shape enterprise MCP architecture, security, governance and integration standards, enabling AI agents and large language models (LLMs) to securely connect with enterprise applications, data platforms and services. You will collaborate with AI Engineering, Enterprise Architecture, Cloud Platform, Cybersecurity and cross-functional teams to accelerate responsible AI adoption.

Requirements

Bachelor's degree in computer science, software engineering, data engineering, information systems or a related technical field, or equivalent practical experience.
Minimum 5 years' 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, 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, with 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 connecting 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, and 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.