Lead Enterprise Architect – AI Solutions

Lead Enterprise Architect for AI Solutions at MetLife, focusing on driving enterprise and solution architecture for AI/ML and Generative AI initiatives within the Retirement Income Solutions business. This role involves defining architectural roadmaps, guiding the adoption of modern cloud-native architectures, and establishing architecture standards. The architect will also mentor other architects and engineers, and has experience with AI/ML solutions, model integration, prompt engineering, AI governance, and agentic frameworks for enterprise automation.

What you'd actually do

  1. Lead the development of multi‑year enterprise and solution architecture roadmaps aligned to line‑of‑business strategic and tactical priorities.
  2. Design and deliver secure, scalable, and fit‑for‑purpose solution architectures within an agile delivery model, partnering closely with business, engineering, and application teams.
  3. Guide the adoption of modern, cloud‑native architectures (preferably Microsoft Azure), including PaaS‑focused solutions and enterprise cloud standards.
  4. Establish and evolve architecture standards, patterns, governance, and best practices across U.S. Technology Architecture.
  5. Mentor and influence architects and engineers by raising technical standards through hands‑on guidance, training, and thought leadership.

Skills

Required

  • Bachelor’s degree in an engineering discipline (CS, EE, ME, Math, or equivalent).
  • 7 years of experience in architecting, engineering, and delivering enterprise business solutions.
  • Proven experience designing and operationalizing AI/ML and Generative AI solutions, including model integration, prompt engineering, and AI governance.
  • Experience designing and engineering across multiple technology domains, including application, data, security, cloud/infrastructure and experience with event-driven architectures, microservices, and API ecosystems.
  • Ability to prototype concepts, run POCs, and translate ideas into actionable architecture for AD teams (not day-to-day coding).

Nice to have

  • Hands on experience with enterprise solutions in the cloud, including IaaS, SaaS, and PaaS technologies
  • Experience with agentic frameworks (e.g., autonomous agents, orchestration frameworks) to support enterprise automation and intelligent workflows
  • Industry experience in Finance/ Insurance/Annuities with a strong understanding of sector-specific challenges.

What the JD emphasized

  • Proven experience designing and operationalizing AI/ML and Generative AI solutions
  • model integration
  • prompt engineering
  • AI governance
  • agentic frameworks

Other signals

  • driving enterprise and solution architecture
  • architectural roadmaps
  • AI/ML and Generative AI solutions
  • model integration
  • prompt engineering
  • AI governance
  • agentic frameworks
  • enterprise automation
  • intelligent workflows