AI Architect

As AI Architect at AXIS Capital, you will shape and govern the company’s AI landscape, turning business opportunities into practical designs. You’ll collaborate across architecture, engineering, data, security, risk and business teams to ensure safe, scalable AI capabilities. You will define reusable patterns, guardrails and governance while guiding teams toward shared, enterprise-wide solutions. This role combines technical leadership with risk-aware decision making in a regulated industry. You will have a clear opportunity to influence how AI drives decision-making, customer service and risk management.

• medical plans for you and your family
• health and wellness programs
• retirement plans
• tuition reimbursement
• paid annual leave
• competitive benefits package

• Design secure, scalable AI architectures across generative AI, ML, automation and agent-based use cases
• Translate business needs into clear AI designs and communicate trade-offs to technical and non-technical stakeholders
• Define and promote reusable AI patterns, components, standards and guardrails (model selection, orchestration, grounding, observability, human oversight)
• Identify cross-team requirements and shape reusable components and reference implementations
• Provide architectural oversight to minimize duplication and guide toward shared capabilities
• Advise on responsible AI practices (fairness, explainability, privacy, security, safety, regulatory compliance and human oversight)
• Assess AI use cases for suitability and recommend simpler, higher-value approaches when appropriate
• Architect AI solutions that securely integrate with enterprise data, apps, APIs and workflows
• Support solution teams with retrieval-augmented generation, semantic search, prompt/context management, model evaluation, MLOps/LLMOps
• Ensure testing, monitoring, cost control, performance, resilience, auditability and lifecycle management are built in
• Contribute to AI governance and design assurance, including proposals to risk review forums and documenting key decisions
• Evaluate emerging AI tech and vendors through structured assessments and proofs of concept
• Collaborate with engineers and delivery teams to resolve design issues while maintaining enterprise standards
• Build trusted relationships with business and tech stakeholders and facilitate value-focused workshops
• Stay informed on AI tech, industry practices and regulation to evolve AXIS's architecture guidance
• Additional duties as needed

• 5+ years in AI/ML, data science, software engineering or solution architecture with experience delivering AI-enabled solutions
• Strong technical foundation across software engineering, cloud platforms, APIs, data integration, security and modern development practices
• Hands-on experience with Databricks and Azure platforms
• Proven ability to design enterprise-grade AI architectures with security, scalability, performance, observability, governance and cost control
• Working knowledge of LLMs, embeddings, vector search, retrieval-augmented generation, agents, evaluation and prompt design
• Experience designing on major cloud platforms; familiarity with Microsoft Azure and its AI ecosystem
• Understanding of MLOps/LLMOps, versioning, testing, deployment, monitoring and lifecycle management
• Knowledge of responsible AI principles (privacy, security, fairness, explainability, transparency, safety, human oversight)
• Ability to evaluate AI use cases for value, data dependencies and operational impact
• Experience creating architecture artefacts (solution designs, data flows, standards, reusable patterns) and working within AI governance environments
• Strong stakeholder management, workshop facilitation and ability to communicate complex AI concepts to non-technical audiences
• Collaborative, pragmatic approach balancing governance and delivery across multiple initiatives
• Curiosity and sound judgement with a willingness to continuously learn in a changing landscape

• Stakeholder management
• Workshop facilitation
• Clear communication
• Azure AI ecosystem
• Databricks
• Generative AI concepts (LLMs, embeddings)