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# Associate Director, AI Solution Architecture

- **Company:** Blue Cross and Blue shield of Massachusetts, Inc.
- **Location:** Boston, MA, United States
- **Experience:** Experienced
- **Salary:** $215,010.0 - $262,790.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Cloud Computing, Cloud Storage, Encodings, Databases, Data Retrieval, Machine Learning, Cloud Services, Software Engineering, Systems Integration, Pinecone, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, IT Architecture, Llamaindex, Agentic-AI, Vertex AI Vector Search, Information Technology, Google Cloud Functions, Machine Learning Operations, Api Design, Microservices
- **Published:** October 1, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18486566?backUrl=%2Fcareer%2F18486566%2FAssociate-Director-Ai-Solution-Architecture-Massachusetts-Boston

## About the Role

* Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related technical field (or equivalent practical experience).
 * 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.
 * Leadership: 3+ years of experience directly managing and leading teams of technical architects or systems designers.
 * Cloud Expertise: Hands-on architectural experience with Google Cloud Platform (GCP) services, including Vertex AI Agent Builder, Vertex AI Search, BigQuery, Cloud Storage, and Cloud Run.
 * AI Architecture: Proven expertise in designing solution architectures leveraging Large Language Models (LLMs), including RAG, embeddings, complex function calling, and multi-agent frameworks.
 * Integration & Systems: Strong command of API design, microservices, cloud-native development patterns, and integrating AI capabilities into existing enterprise product ecosystems.
 * MLOps Foundations: Solid knowledge of MLOps practices, including designing frameworks to measure and monitor LLM quality, latency, and cost in production.
 * Communication: Exceptional ability to translate ambiguous business problems into structured technical architectures and present them clearly to diverse audiences., * Certifications: Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer.
 * Advanced AI Orchestration: Deep exposure to designing architecture for autonomous tool-use patterns and frameworks such as Google ADK, LangChain, or LlamaIndex.
 * Data Retrieval: Experience integrating and scaling enterprise vector databases (e.g., Vertex AI Vector Search, AlloyDB, Pinecone) for high-performance, embedding-based retrieval.
 * Regulated Industries: Experience working in healthcare, insurance, or finance, with a strong understanding of data privacy frameworks (e.g., HIPAA) and compliance requirements in solution design., High school degree or equivalent required unless otherwise noted above

## Description

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.
What You'll Do

 * Team Leadership & Mentorship: Lead, mentor, and manage a high-performing team of AI solution architects, providing technical guidance, architectural oversight, and career development.
 * Solution Design & Engineering Partnership: 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.
 * Architect Agentic Solutions: Oversee the architectural design of AI assistants, establishing enterprise best practices for model selection, prompt orchestration, retrieval-augmented generation (RAG), and agent orchestration.
 * Multi-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.
 * System Integration: Architect secure, scalable tool-use and function-calling patterns, ensuring AI agents connect seamlessly to enterprise APIs, databases, and third-party systems.
 * Responsible AI & Governance: Partner with AI Governance to structurally embed ethical considerations, fairness, transparency, hallucination mitigation, and strict data privacy into all AI solutions.
 * Production Scalability: Design highly available, production-grade solutions, collaborating closely with engineering leads to ensure architectural concepts translate into reliable, high-performance deployments.
 * Communication: 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.