Lead Architect - Generative AI

Iberdrola•Boston, MA

2d•$116,640 - $167,600•Onsite

About The Position

The Lead Architect - Generative AI leads the development of generative AI platforms and software solutions for Avangrid customers, combining strategic leadership, technical expertise, and operational excellence. The role owns the technical foundation for AI-native experiences, including knowledge systems and decision logic that enable reliable, scalable AI across business functions. It reports to the Manager - Application Development and is based in an office in Orange, Connecticut; Rochester, New York; or Boston, Massachusetts.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related technical discipline with 10+ years of professional experience, or a master’s degree with 7+ years of experience.
5–7 years of experience in a senior engineering or technical leadership role.
Expert software development experience leveraging Agile DevOps practices for CI/CD.
Proven track record of building and deploying AI-powered systems or workflow automation solutions in a production environment.

Nice To Haves

Experience with Generative AI and Large Language Models (LLMs).

Responsibilities

Lead the strategic direction for engineering and digital operations, aligning AI advancements with business goals.
Design and optimize how AI agents reason, retrieve information, and act within production systems.
Architect connections between AI agents and external enterprise systems, defining authentication patterns, error handling, and data transformation standards.
Develop approaches to versioning, A/B testing, and performance evaluation to ensure consistency and accuracy across AI scenarios.
Provide expert guidance on generative AI best practices, advanced technologies, and emerging trends.
Oversee AI solutions from ideation and data foundations through production-grade deployment.
Establish technical guardrails and safety frameworks to prevent unintended AI behavior and ensure regulatory compliance.
Implement observability to turn AI system behavior into actionable insights and measurable improvements.
Reduce technical debt while keeping AI systems reliable and stable during peak operational seasons.
Support configuration and deployment of automated workflows and AI-powered applications across the enterprise.
Partner with business unit leaders to understand pain points and translate them into scalable AI use cases.
Communicate AI strategy, technical progress, and business impact to executive leadership.