Senior AI Solution Architect

Boston ScientificArden Hills, MN
$106,800 - $202,900Hybrid

About The Position

Boston Scientific is seeking a Senior 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 operate at the intersection of business strategy and advanced technology — translating complex 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 across engineering, data, cybersecurity, legal and business teams.

Requirements

  • Minimum 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.
  • Previous background in healthcare, life sciences or other highly regulated industries.
  • 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.

Nice To Haves

  • 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.
  • Preferred hands-on experience with MLOps/LLMOps, including model monitoring, evaluation and lifecycle management.
  • Proven experience defining reference architectures, design patterns and reusable AI platforms.

Responsibilities

  • 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 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, ensuring measurable business impact.
  • Collaborate with AI engineers, software engineers, data scientists and data engineers to guide implementation and ensure architectural integrity.
  • Partner with enterprise architecture, cybersecurity, legal, privacy, quality and platform engineering teams to 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 all solution architectures.
  • Support risk assessments, model reviews and required documentation for enterprise and regulated environments.

Benefits

  • Access to the latest tools, information and training
  • Support in advancing skills and career
  • Support in progressing
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