AI Solutions Delivery Engineer

AI Solutions Delivery Engineer

Boston Scientific's Active Implantable Systems (AIS) R&D organization is seeking an AI Solutions Delivery engineer to join our AI Transformation core team and implement, integrate and sustain the AI-assisted engineering platform. This is an exciting opportunity to join a growing team that will enable the re-imaging of how work gets done across our R&D engineering functions. You will configure tools, build integrations and enable pilot workflows, working closely with the AI Solutions Architect on design standards and with the AI Solutions Lead on translating validated pilot designs into running, supported capabilities.

This is a hands-on delivery role responsible for the day-to-day reliability of the platform as it scales from pilot to production. You will manage solution reliability, observability, performance evaluation, user access and issue resolution across the R&D engineering ecosystem. The work will require you to coordinate closely with Enterprise AI and IT teams on tool integrations across our engineering ecosystem consisting of a mix of SaaS and custom tool solutions.

At Boston Scientific, we value collaboration and synergy. This role follows an onsite work model requiring employees to be in our local office 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. Relocation assistance is not available for this position at this time.

Your responsibilities will include:

• Implement and sustain the AI-assisted engineering platform, including tool configuration and workflow enablement during pilots.
• Build and maintain integrations between the AI platform and enterprise engineering systems, including Windchill, Jira, Git Lab, AWS, Azure and other tools.
• Manage solution reliability, monitoring and issue resolution as workflows move from pilot to production.
• Manage user access, permissions and onboarding for platform users across AIS R&D functions.
• Coordinate with Enterprise AI and IT teams on platform alignment, tool governance and enterprise non-negotiables.
• Partner with the AI Solutions Architect to implement architecture direction, design standards and integration patterns.
• Partner with the AI Solutions Lead to operationalize validated pilot designs into supported, production-ready capabilities.
• Operationalize reliability, access management and issue resolution practices at scale as the number of in-scope workflows grows.
• Contribute to a culture of ownership, experimentation and operational excellence.

Required qualifications:

• Bachelor's degree in computer science, engineering or a related technical field.
• Minimum of 3 years' experience building, deploying or operating production software or platform services.
• Experience integrating enterprise systems and tools (e.g., PLM/Windchill, Jira, Git Lab, CI/CD platforms, Snowflake) into a shared platform or service.
• Experience with cloud infrastructure (AWS, Azure or similar), including deployment, monitoring and access management.
• Experience troubleshooting production issues, including monitoring, alerting and incident response.
• Ability to operate with a high degree of autonomy in a fast-moving, evolving technical environment.
• Experience integrating or supporting AI/LLM tools, copilots or agentic workflows in production.
• Experience with Dev Ops practices, infrastructure as code and CI/CD pipeline design.
• Demonstrated proficiency using agentic AI tools and platforms to deliver solutions in area of expertise.

Preferred qualifications:

• Experience working in a regulated, enterprise-scale environment with security, compliance and quality requirements.
• Experience supporting PLM systems (e.g., Windchill) or other engineering tool ecosystems in a medical device or life sciences environment.
• Familiarity with vector databases, model serving or LLM gateway/routing patterns.
• Scripting and automation experience to reduce manual operational overhead.