Senior AI Solutions Lead

Senior AI Solutions Lead

Boston Scientific's Active Implantable Systems (AIS) R&D organization is seeking a Senior AI Solutions Lead to join our AI Transformation core team and translate engineering workflow requirements into AI solution designs. 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. In this role, you will act as the domain-grounded bridge between our AIS R&D engineering functions (systems, software, hardware, research and PMO) and the AI Solutions Architect and AI Solutions Delivery roles, leading solution design for pilot workflows and coordinating input from domain subject matter experts.

You will evaluate tool configurations and integration patterns for each candidate workflow, support pilot design and evidence capture, and help validate results from the evaluation harness before workflows scale to production. The role requires strong hands-on applied AI or ML engineering skills combined with the ability to translate ambiguous engineering requirements into concrete, testable AI solution designs within a regulated product development environment.

Your responsibilities will include:

• Translate engineering workflow requirements from AIS R&D domain SMEs into concrete AI solution designs.
• Evaluate tools, configurations and integration patterns for each candidate workflow, including build-versus-reuse recommendations.
• Lead and coordinate AIS R&D domain SME input throughout pilot design, evaluation and rollout.
• Support pilot design and evidence capture, including defining success criteria and test scenarios for candidate workflows.
• Validate results from the evaluation harness and help resolve issues identified during pilot testing.
• Design and deploy retrieval-augmented generation, context engineering and model integration patterns for engineering use cases.
• Partner with the AI Solutions Architect on architecture direction, and with AI Solutions Delivery on implementation and operational hand-off.
• Hand off validated domain playbooks to functional teams as workflows move from pilot to production.
• Contribute to a culture of ownership, experimentation and customer-centric solution design.

Qualifications:

• Bachelor's or master's degree in computer science, engineering, data science or a related technical field.
• Minimum of 5 years' experience in AI/ML engineering, solution design or applied AI development, including recent hands-on work in generative AI.
• Proven experience designing and deploying large language model-based solutions, including retrieval-augmented generation, context engineering, and model integration.
• Experience translating business or engineering requirements into technical solution designs and working directly with subject matter experts.
• Experience building or supporting pilot evaluations, including defining success metrics and capturing evidence for go/no-go decisions.
• Experience working in a regulated, enterprise-scale environment with security, compliance and quality requirements.
• Strong communication skills, with the ability to explain technical AI concepts to non-technical engineering stakeholders.

• Proven experience with agentic AI frameworks such as Lang Graph, Semantic Kernel, Auto Gen, CrewAI or similar technologies.
• Familiarity with vector databases, embedding strategies and search optimization techniques.
• Hands-on experience with MLOps/LLMOps, including model monitoring, evaluation and lifecycle management.
• Experience in health care, life sciences, medical devices or another highly regulated industry.
• Experience coordinating cross-functional technical SMEs across multiple engineering disciplines.