Senior Platform Engineer - Enterprise AI
Boston Scientific17 days ago
Arden Hills, MN, USASenior
Base Salary
$89k - $170k/yr
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, Microsoft 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 covering 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.
Requirements
- Bachelor’s degree in computer science, software engineering, data engineering, information systems, or a related technical field, or equivalent practical experience.
- Minimum five 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, AI agents, LLMs, retrieval-augmented generation, and agentic AI architectures.
- Expertise in at least two cloud platforms, including AWS and Microsoft Azure.
- Strong knowledge of enterprise APIs, microservices, distributed systems, and integration architecture.
- Experience with OAuth/OIDC, identity and access management, RBAC/ABAC, and Zero Trust security.
- Proficiency with Kubernetes, containers, CI/CD, and infrastructure-as-code.
- Experience developing enterprise architecture standards, governance frameworks, and technology roadmaps.
- Strong communication and stakeholder-management skills with the ability to influence technical leadership.
- Preferred experience designing enterprise generative AI or agent platforms.
- Preferred hands-on experience with MCP clients, servers, gateways, or related AI integration technologies.
- Preferred experience with API management, service mesh, and multi-cloud architectures.
- Preferred familiarity with OpenTelemetry, Fiddler, or enterprise observability platforms.
- Preferred knowledge of responsible AI, AI governance, and emerging agent-security practices.
Benefits
- Hybrid work model requiring employees to work at the Arden Hills, Minnesota or Marlborough, Massachusetts office at least three days per week.
- Boston Scientific employee benefits are available through its benefits program; compensation and benefits vary by location and other factors.
Tech Stack
Categories
About Boston Scientific
Boston Scientific designs and manufactures implantable and minimally invasive medical devices used by physicians to diagnose and treat cardiovascular, endoscopic, urological, neurological, and other conditions. It sells these products and related therapies to hospitals and health systems worldwide through a direct sales model and distributors. Founded in 1979 and headquartered in Marlborough, Massachusetts, it is publicly traded on the NYSE (BSX) with offerings spanning stents, catheters, electrophysiology, and neuromodulation systems.