Senior Platform Engineer - Enterprise AI & Multi-Cloud
Boston Scientific
Summary
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.
Job description
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 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.
Preferred qualifications:
- 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.
Requirements
- 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 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.
Benefits
- Health insurance
- Professional development
- Training opportunities
- Annual bonus target
- Long-term incentives
Company overview
Boston Scientific Corporation is a global leader in the development, manufacturing, and marketing of minimally invasive medical devices used in interventional medical specialties. Founded in 1979 and headquartered in Marlborough, Massachusetts, the company focuses on transforming patient lives through innovative medical solutions across a wide range of therapeutic areas including cardiology, endoscopy, urology, pulmonology, and neuromodulation. With approximately 53,000 employees worldwide and operations in 40 countries, Boston Scientific serves over 44 million patients annually. The company invests heavily in research and development, allocating $1.6 billion to R&D in 2024, and maintains a strong commitment to quality, patient safety, and meaningful innovation. Boston Scientific's product portfolio includes advanced technologies such as cardiac rhythm management devices, coronary stents, ablation systems, endoscopy equipment, and neuromodulation therapies, all designed to improve patient outcomes and quality of life through less invasive treatment options.