Associate Director, AI Solution Architecture

Blue Cross Blue Shield of Massachusetts•Boston, MA

1d•Hybrid

About The Position

This role has an in office expectation of 2X a week in our Boston location. We are in the office on Tuesdays and Wednesdays. We are looking for an Associate Director, AI Solution Architecture to lead our Enterprise AI and Solution Architecture group. In this leadership role, you will translate enterprise AI strategy into coherent, governed, and production-viable solution architectures that span business lines, platforms, and geographies. This role does not build the core platform or own feature delivery; rather, you will define how AI capabilities are assembled into complete, end-to-end business solutions. Operating as a critical technical peer to the AI engineering and delivery function, you will bridge the gap between complex business needs and scalable architecture to drive the adoption of intelligent AI assistants and agentic workflows across the enterprise.

Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related technical field (or equivalent practical experience).
8+ years in software engineering or solution architecture, with 3+ years specifically focused on designing large-scale AI/ML or LLM-based agentic solutions.
3+ years of experience directly managing and leading teams of technical architects or systems designers.
Hands-on architectural experience with Google Cloud Platform (GCP) services, including Vertex AI Agent Builder, Vertex AI Search, BigQuery, Cloud Storage, and Cloud Run.
Proven expertise in designing solution architectures leveraging Large Language Models (LLMs), including RAG, embeddings, complex function calling, and multi-agent frameworks.
Strong command of API design, microservices, cloud-native development patterns, and integrating AI capabilities into existing enterprise product ecosystems.
Solid knowledge of MLOps practices, including designing frameworks to measure and monitor LLM quality, latency, and cost in production.
Exceptional ability to translate ambiguous business problems into structured technical architectures and present them clearly to diverse audiences.

Nice To Haves

Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer.
Deep exposure to designing architecture for autonomous tool-use patterns and frameworks such as Google ADK, LangChain, or LlamaIndex.
Experience integrating and scaling enterprise vector databases (e.g., Vertex AI Vector Search, AlloyDB, Pinecone) for high-performance, embedding-based retrieval.
Experience working in healthcare, insurance, or finance, with a strong understanding of data privacy frameworks (e.g., HIPAA) and compliance requirements in solution design.

Responsibilities

Lead, mentor, and manage a high-performing team of AI solution architects, providing technical guidance, architectural oversight, and career development.
Partner with the AI Engineering team to conduct business needs assessments and identify high-impact agentic use cases. Translate complex business requirements into robust, scalable technical blueprints that enable production-grade engineering delivery.
Oversee the architectural design of AI assistants, establishing enterprise best practices for model selection, prompt orchestration, retrieval-augmented generation (RAG), and agent orchestration.
Guide the design of intelligent, multi-step AI agents, defining patterns for sequential, loop, parallel, and hierarchical architectures to handle multi-turn, multi-domain use cases.
Architect secure, scalable tool-use and function-calling patterns, ensuring AI agents connect seamlessly to enterprise APIs, databases, and third-party systems.
Partner with AI Governance to structurally embed ethical considerations, fairness, transparency, hallucination mitigation, and strict data privacy into all AI solutions.
Design highly available, production-grade solutions, collaborating closely with engineering leads to ensure architectural concepts translate into reliable, high-performance deployments.
Serve as the primary architectural liaison, effectively articulating the value, mechanics, and design of agentic AI solutions to non-technical business leaders and executive stakeholders.