Sr. AI Engineer

Ready to help us transform healthcare? Bring your true colors to blue. What We Need We are looking for an AI Sr. Engineer to lead one or more of our high-performing AI engineering teams at Blue Cross Blue Shield of Massachusetts. You'll be a hands-on technical leader — combining deep expertise in machine learning, agentic AI systems, and cloud platforms with strong mentorship skills to guide a talented group of engineers. This role sits at the heart of our AI initiatives, where you'll drive technical excellence while building innovative solutions that directly impact our members and the healthcare industry. You'll own the technical direction, delivery, and quality of your team's work, ensuring our AI solutions are well-architected, scalable, and production-grade. This is a critical role for someone who is equally comfortable writing code and reviewing architecture, mentoring junior engineers, and making technology decisions that shape our AI platform for years to come. Your Day to Day · Provide technical leadership  — Guide and mentor a team of AI Engineers; establish and enforce architectural best practices, coding standards, and engineering excellence; conduct code reviews that elevate team capability · Lead solution design  — Own the detailed technical design and implementation of complex agentic AI systems, Generative AI integrations, RAG architectures, and infrastructure; make technology and framework decisions with your team · Oversee delivery and execution  — Collaborate closely with Product Owners to refine technical requirements, estimate effort, and deliver high-quality AI features on time; balance quality with velocity · Build scalable AI systems  — Design and implement production-grade AI agents and models; manage performance, scalability, and reliability; establish monitoring, evaluation, and observability for AI workloads · Troubleshoot complex problems  — Serve as the primary technical escalation point; debug complex issues in ML pipelines, agent systems, cloud infrastructure, and integrate systems; guide your team to solutions · Hands-on coding  — Spend 40-50% of your time writing code alongside your team; stay grounded in day-to-day engineering challenges and remain credible as a technical leader · Mentor and grow talent  — Actively coach AI Engineers; help them develop deeper expertise in ML fundamentals, agentic architectures, cloud platforms, and system design; create learning opportunities and growth paths · Evaluate new technologies  — Stay current on emerging tools, frameworks, and libraries (new agent frameworks, LLMs, MLOps platforms); assess fit for our platform and recommend adoption when valuable · Drive engineering practices  — Establish rigorous code review processes, knowledge-sharing sessions, documentation standards, and testing practices that scale as the team grows · Collaborate across teams  — Partner with Data Engineering, Platform Engineering, Product, and Operations to ensure AI solutions…