Senior AI Solution Architect
Boston Scientific
Summary
Boston Scientific is seeking an AI solution architect to join our AI Engineering team and lead the design of next-generation AI solutions across the enterprise. In this role, you will bridge the gap between complex business needs and advanced AI system design, translating business challenges into scalable, secure and compliant generative AI and agentic AI architectures. You will define end-to-end technical solution architectures for AI-powered products, including custom generative AI applications, intelligent agents, virtual assistants and reusable AI services. This role requires deep technical expertise, strong architectural judgment and the ability to influence cross-functional stakeholders.
Job description
Your responsibilities will include:
- Lead the end-to-end architecture of enterprise AI solutions, including generative AI applications, large language model-powered workflows, agentic systems and intelligent automation.
- Design modular and reusable AI components and services that can be leveraged across multiple platforms and business use cases.
- Define architectural patterns for agent orchestration, tool integration, memory management, retrieval-augmented generation and human-in-the-loop workflows.
- Translate business requirements into scalable, production-ready AI architectures aligned with enterprise standards.
- Partner with business stakeholders to understand objectives, constraints and value drivers, helping ensure measurable business impact.
- Collaborate with AI engineers, software engineers, data scientists and data engineers to guide implementation and maintain architectural integrity.
- Partner with enterprise architecture, cybersecurity, legal, privacy, quality and platform engineering teams to help ensure solutions meet regulatory, security and quality expectations.
- Architect secure and scalable data pipelines in partnership with data engineering teams to support AI and generative AI workloads.
- Evaluate and integrate technologies across Azure, AWS and Snowflake to deliver cloud-native, resilient and cost-effective solutions.
- Guide platform-level decisions related to model hosting, vector databases, orchestration frameworks, monitoring and MLOps/LLMOps practices.
- Ensure solutions are designed for performance, reliability, observability and operational excellence.
- Embed ethical AI, security-by-design, privacy-by-design and compliance-by-design principles into solution architectures.
- Support risk assessments, model reviews and required documentation for enterprise and regulated environments.
Required qualifications:
- Bachelor’s or master’s degree in computer science, engineering, data science or a related technical field.
- Minimum of 5 years' experience in solution architecture, software architecture or AI/ML engineering, including recent hands-on work in generative AI.
- Proven experience designing and deploying large language model-based solutions, including retrieval-augmented generation, prompt engineering and model integration.
- Experience in health care, life sciences or another highly regulated industry.
- Strong understanding of cloud-native architectures in Azure and/or AWS and modern data platforms such as Snowflake.
- Demonstrated experience working in enterprise-scale, regulated environments with security, compliance and quality requirements.
- Demonstrated ability to communicate complex technical concepts clearly to technical and nontechnical audiences.
Preferred qualifications:
- Proven experience with agentic AI frameworks such as LangGraph, Semantic Kernel, AutoGen, 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.
- Proven experience defining reference architectures, design patterns and reusable AI platforms.
Requirements
- Bachelor’s or master’s degree in computer science, engineering, data science or a related technical field.
- Minimum of 5 years' experience in solution architecture, software architecture or AI/ML engineering, including recent hands-on work in generative AI.
- Proven experience designing and deploying large language model-based solutions, including retrieval-augmented generation, prompt engineering and model integration.
- Experience in health care, life sciences or another highly regulated industry.
- Strong understanding of cloud-native architectures in Azure and/or AWS and modern data platforms such as Snowflake.
- Demonstrated experience working in enterprise-scale, regulated environments with security, compliance and quality requirements.
- Demonstrated ability to communicate complex technical concepts clearly to technical and nontechnical audiences.
- Proven experience with agentic AI frameworks such as LangGraph, Semantic Kernel, AutoGen, 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.
- Proven experience defining reference architectures, design patterns and reusable AI platforms.
Benefits
- Health Insurance
- Annual Bonus
- 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.