Senior AI Architect — Generative & Agentic Solutions

Boston Scientific; Marlborough (MA); Hybrid; USD 107,000 - 203,000; Full time

Job summary

Boston Scientific is seeking an AI solution architect to join its AI Engineering team and lead the design of next-generation AI solutions across the enterprise. You will bridge complex business needs with scalable, secure AI architectures and guide end-to-end implementations.

The role requires deep technical expertise in generative AI, LLM workflows, cloud platforms (Azure/AWS) and collaboration with data scientists, software engineers and cybersecurity to ensure compliance and performance.

Qualifications

• Minimum of 5 years in solution/ software architecture or AI/ML engineering, with recent generative AI work.
• Experience designing and deploying LLM-based solutions including retrieval augmented generation.
• Experience in health care, life sciences or a regulated industry.
• Strong cloud-native architectures in Azure/AWS and data platforms like Snowflake.

Responsibilities

• Lead end-to-end architecture of enterprise AI solutions including generative AI apps and agentic systems.
• Design modular AI components and services for multiple platforms and use cases.
• Define patterns for agent orchestration, memory, retrieval-augmented generation and human-in-the-loop workflows.
• Translate business requirements into scalable, production-ready AI architectures.
• Collaborate with stakeholders to ensure measurable business impact and regulatory compliance.
• Guide engineers across AI, software, data teams to maintain architectural integrity.

Skills

Solution architecture

AI/ML engineering

Cloud integration

Communication

Education

Bachelor’s or Master’s in CS/Engineering/Data Science

Tools

Azure

AWS

Snowflake

LangGraph

Semantic Kernel

AutoGen

CrewAI

Job description

Boston Scientific is seeking an AI solution architect to join its AI Engineering team and lead the design of next-generation AI solutions across the enterprise. You will bridge complex business needs with scalable, secure AI architectures and guide end-to-end implementations.

The role requires deep technical expertise in generative AI, LLM workflows, cloud platforms (Azure/AWS) and collaboration with data scientists, software engineers and cybersecurity to ensure compliance and performance.