AI Architect
Marsh & McLennan Companies2 hours ago
Dublin, Ireland or Charlotte, NC, USAStaff+
Responsibilities
- Own AI platform architecture domains, including integration with Marsh’s existing technology landscape.
- Evaluate emerging AI technologies and define criteria for proofs of concept.
- Collaborate with software engineers on focused proofs of concept, owning integration patterns, deployment topology, and architectural fit.
- Build and maintain reference architectures, integration diagrams, and technology radar documents.
- Create architecture documentation usable by human engineers and AI coding agents.
- Present technical recommendations and contribute agenda items at architecture, developer, and business forums.
- Understand Marsh’s enterprise architecture and design integration patterns compatible with current systems.
- Coach colleagues and share architectural knowledge within the AI Center of Excellence.
Requirements
- Professional experience in software engineering, architecture, or technical design with a track record of contributing to design decisions.
- Professional experience designing or contributing to system architecture, including integration patterns, component decomposition, or technology selection.
- Understanding of cloud-native architecture across AWS, Azure, and GCP.
- Hands-on familiarity with AI coding platforms and copilots such as GitHub Copilot, Claude Code, or Cursor, as well as the modern languages they support.
- Strong intellectual curiosity, technical judgment, communication skills, and ability to evaluate new technologies quickly.
- Preferred experience with AI/ML technologies, including LLMs, RAG, embeddings, or agent frameworks.
- Preferred familiarity with enterprise architecture and architecture documentation for AI agents and humans.
- Cloud architecture certifications such as AWS Solutions Architect or Azure Solutions Architect are preferred.
- Experience presenting at internal architecture forums, technology talks, or external conferences is preferred.
Benefits
- Access to AI models, tools, tokens, and broader professional development opportunities.
- Professional development opportunities, interesting work, and supportive leaders.
- Inclusive and flexible work environment with equal-opportunity and reasonable-accommodation support.
- Hybrid work arrangement with remote flexibility; colleagues are expected to work in a local office or onsite with clients at least three days per week, and office-based teams identify at least one weekly anchor day.
Tech Stack
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