Senior Platform Engineer - Enterprise AI & Multi-Cloud

Additional Location(s):  N/ADiversity
- Innovation
- Caring
- Global Collaboration
- Winning Spirit
- High Performance At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.

About the role:

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.

Work mode and visa sponsorship:

At Boston Scientific, we value collaboration and synergy. This role follows a hybrid work model requiring employees to be in our local office Marlborough, MA at least three days per week. Boston Scientific will not offer sponsorship or take over sponsorship of an employment visa for this position at this time.

Your responsibilities will include:

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, Google Cloud Platform (GCP), 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.

Required qualifications:

Bachelor's degree in computer science, software engineering, data engineering, information systems or a related technical field, or equivalent practical experience. Minimum 8 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 or GCP.Strong knowledge of enterprise APIs, microservices, distributed systems and integration architecture.

Experience with OAuth/OIDC, identity and access management (IAM), role-based and…