Overview In this role, you will lead the Enterprise AI Solution Architecture team to translate AI strategy into production-ready architectures across lines and geographies. You'll work as a technical peer to AI engineering to ensure scalable, end-to-end business solutions rather than building the core platform. You will champion responsible AI, governance, and secure integration while driving adoption of agentic AI across the enterprise. This is a hybrid Boston role with in-office days, offering a chance to shape transformative healthcare AI initiatives.
Compensation / Benefits- paid time off
- medical/dental/vision insurance
- 401(k)
- well-being benefits
Responsibilities- Lead and mentor a high-performing team of AI solution architects
- Partner with AI Engineering to identify high-impact agentic use cases
- Translate business requirements into robust, scalable technical blueprints for production delivery
- Oversee architectural design of AI assistants including model selection, prompt orchestration, RAG, and agent orchestration
- Guide multi-agent orchestration patterns for sequential, loop, parallel, and hierarchical architectures
- Architect secure, scalable tool-use and function-calling patterns connecting AI agents to enterprise APIs, databases, and third-party systems
- Embed Responsible AI & governance, including fairness, transparency, hallucination mitigation, and data privacy
- Design highly available, production-grade solutions with close collaboration with engineering leads
- Articulate architecture value and design to non-technical business leaders and executives
Key requirements- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent practical experience)
- 8+ years in software engineering or solution architecture
- 3+ years leading technical architects or systems designers
- Hands-on architectural experience with Google Cloud Platform (GCP) including Vertex AI Agent Builder, Vertex AI Search, BigQuery, Cloud Storage, Cloud Run
- Proven expertise in designing architectures leveraging Large Language Models (LLMs), including RAG, embeddings, function calling, and multi-agent frameworks
- Strong API design, microservices, cloud-native development patterns, and enterprise integration
- Solid knowledge of MLOps practices for measuring and monitoring LLM quality, latency, and cost in production
- Excellent ability to translate ambiguous business problems into structured technical architectures for diverse audiences
- Strategic leadership
- Strong communication to executives
- Cross-functional collaboration
- Vertex AI Agent Builder
- Vertex AI Search
- BigQuery
