AI Analyst - Architecture

2 hours ago

Dublin, IrelandEntry Level

Responsibilities

Contribute to AI platform architecture and integration patterns across Marsh’s technology landscape.
Research emerging AI technologies, including LLMs, memory systems, agentic frameworks, and guardrails, and recommend technologies for proof-of-concept evaluation.
Collaborate with software engineers on focused proofs of concept from an architecture and integration perspective.
Build high-level integration diagrams, reference architectures, and technology radar documents.
Create architecture documentation suitable for human engineers and AI coding agents.
Present architecture perspectives at Marsh’s Architecture Council, Dev Council, and business unit forums.
Learn Marsh’s enterprise architecture and ensure recommendations account for the existing technology landscape.

Bachelor’s degree in computer science, software engineering, data science, information systems, or a related discipline; a master’s degree is preferred.
Up to two years of professional experience, including internships and placements.
Genuine interest in system design and architecture, with attention to how systems fit together.
Strong intellectual curiosity, ability to learn quickly, and high standards for quality.
Familiarity with AWS, Azure, or GCP.
Hands-on comfort with AI coding platforms and copilots such as GitHub Copilot, Claude Code, or Cursor, along with the modern languages they support.
Strong written and verbal communication skills.

Professional development opportunities, interesting work, and supportive leaders.
Inclusive and flexible work environment with collaboration and career-development opportunities.
Access to AI models, tools, tokens, and broader professional development opportunities.
Hybrid work with remote flexibility, while colleagues are expected to work from a local office or onsite with clients at least three days per week; office-based teams have at least one weekly anchor day.
Preferred qualifications include AI/ML experience through academic or personal projects involving LLMs, RAG, embeddings, or agent frameworks; enterprise architecture exposure; cloud architecture certifications; and technical presentation experience.

501-1,000 employees