Manager - AI Engineering

Boston Scientific • Georgetown, MA

1d • $106,800 - $202,900 • Hybrid

About The Position

At Boston Scientific, we’re advancing science for life through AI innovation, and we’re seeking a manager who can balance hands-on delivery with visionary leadership to expand our AI capabilities. In this role, you’ll lead a team of engineers building secure, scalable LLM services and data platforms that power real-world impact. Your work will help shape how artificial intelligence improves patient outcomes and drives efficiency across global healthcare systems.

Requirements

• Bachelor’s degree in a relevant field; a science, technology, engineering, or mathematics (STEM) discipline is preferred.
• 8+ years of industry engineering experience beyond academic training.
• 4+ years managing cross-functional AI, data, or software teams with responsibility for performance and team development.
• Hands-on expertise with at least one major cloud (Amazon Web Services, Google Cloud Platform, or Microsoft Azure) and modern data stacks (Apache Spark or Apache Flink; Apache Airflow; Snowflake or BigQuery; Delta Lake).
• Deep understanding of microservices architecture, secure application programming interface (API) design, and regulated data-exchange patterns.
• Strong communication and stakeholder management skills for effective collaboration across global teams and functions.

Nice To Haves

• M.S. in Computer Science, Data Science, or a related field.
• Proven record delivering generative AI solutions, including LLM fine-tuning, RAG, vector search, guardrails, and evaluation frameworks.
• Certifications such as AWS Certified Data Analytics, GCP Professional Machine Learning Engineer, or Azure AI Engineer Associate.
• Experience in highly regulated domains such as healthcare, finance, or government cloud.
• Experience contributing to open-source generative AI projects or publications on enterprise AI best practices.

Responsibilities

• Lead an engineering organization of Data Engineers, Generative-AI Engineers, and Generative-AI Solution Architects (7+ full-time equivalents), fostering a learning-focused, high-performance culture.
• Support product teams with technical requirements and user-story definition to align engineering deliverables with clinical and regulatory needs.
• Serve as the primary liaison between business stakeholders and engineering, translating commercial and clinical priorities into actionable backlogs; communicate progress, risks, and dependencies.
• Define and execute the technical roadmap for data ingestion, feature stores, vector databases, and LLM-powered services; align outcomes to objectives and key results (OKRs) and budget.
• Oversee architecture and code reviews for RAG pipelines, fine-tuning workflows, prompt operations, and model governance to ensure scalability, security, and cost efficiency.
• Embed observability, drift monitoring, and alignment guardrails across data and model lifecycles; target 99.9% uptime and fast mean time to recovery (MTTR).
• Drive machine learning operations (MLOps) and large language model operations (LLMOps), including continuous integration/continuous delivery (CI/CD), model registries, and evaluation suites; optimize graphics processing unit (GPU) and accelerator utilization and cost.
• Partner with Product, Security, and Compliance to convert business needs into AI solutions and clearly communicate risk-reward trade-offs to executive stakeholders.
• Champion continuous learning via brown-bag sessions, conference support, and individualized career-development plans.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager