Beveiliging Architect in London

This is your opportunity to join AXIS Capital - a trusted global provider of specialty lines insurance and reinsurance. We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders. We also proudly maintain an entrepreneurial, disciplined and ethical corporate culture.

About AXIS: This is your opportunity to join AXIS Capital - a leading provider of specialty insurance and global reinsurance. We give people and organisations the confidence to take necessary risks in the pursuit of their goals and ambitions. Our strength is grounded in our people and culture, which encourages collaboration, diversity and entrepreneurialism.

Life at AXIS:

• Hybrid work model: We value work-life balance and offer flexibility to our employees through a hybrid work model.
• Diverse and inclusive environment: We celebrate diversity and strive to create an inclusive environment for all employees.
• Career growth opportunities: We are committed to your professional development and offer opportunities for growth and advancement.
• Social impact initiatives: We believe in making a difference and support various social and environmental causes.

How does this role contribute to our collective success? Artificial intelligence has the potential to improve how AXIS makes decisions, serves customers, manages risk and operates efficiently. Realising that potential requires AI solutions that are useful, secure, responsible and aligned with business outcomes.

The AI Architect will help shape and govern AXIS's AI landscape, translating business opportunities into practical technical designs. The role will work across architecture, engineering, data, security, risk and business teams to ensure AI capabilities are adopted consistently and safely.

Key Responsibilities:

• Design secure, scalable and resilient enterprise-grade AI architectures across generative AI, machine learning, intelligent automation and agent-based use cases.
• Translate business needs into clear AI designs, explaining technical choices, benefits, limitations, risks and trade-offs to both technical and non-technical stakeholders.
• Define and promote reusable AI architecture patterns, shared components, standards and guardrails covering model selection, orchestration, grounding, integration, observability and human oversight.
• Identify common requirements across AI initiatives and shape reusable components, services and reference implementations that can be adopted by multiple teams.
• Maintain architectural oversight across multiple AI projects, identifying duplication and guiding teams towards shared capabilities rather than creating project-specific solutions in isolation.
• Guide teams on responsible AI best practices, including fairness, explainability, transparency, privacy, security, safety, regulatory compliance and appropriate human control.
• Assess whether proposed AI use cases are suitable for AI, and recommend simpler approaches where these offer better value, control or maintainability.
• Architect AI solutions that integrate securely with enterprise data, applications, APIs and workflow platforms, working closely with Data, Integration, Cloud and Security Architecture.
• Ensure designs include appropriate testing, monitoring, cost management, performance, resilience, auditability and lifecycle controls.
• Contribute to AI governance and design assurance, including presenting proposals to architecture and risk review forums and tracking key decisions.
• Evaluate emerging AI technologies and vendors through structured assessments and proofs of concept, balancing innovation with operational and regulatory risk.
• Collaborate with engineers and delivery teams throughout implementation, helping resolve design issues while maintaining alignment to enterprise standards.
• Build trusted relationships across business and technology teams, facilitating workshops and helping stakeholders understand where AI can create measurable value.
• Maintain awareness of developments in AI technology, industry practice and regulation, and use this knowledge to evolve AXIS's architecture guidance.

What you need to have:

• At least 5 years of relevant experience in AI, machine learning, data science, software engineering, cloud architecture or solution architecture, including experience designing or delivering AI-enabled solutions.
• A strong technical background, with practical understanding of software engineering, cloud platforms, APIs, data integration, security and modern development practices.
• Experience building / designing solutions across a hybrid of Databricks and Azure platforms.
• Proven experience designing enterprise-grade AI architectures that meet requirements for security, scalability, resilience, performance, observability, integration, governance and cost control.
• Working knowledge of generative AI and machine learning concepts, including large language models, embeddings, vector search, retrieval-augmented generation, agents, model evaluation and prompt design.
• Knowledge of Microsoft Azure and its AI ecosystem is particularly relevant to the AXIS technology landscape.
• Understanding of AI delivery and operational practices, including MLOps or LLMOps, versioning, testing, deployment, monitoring, observability and lifecycle management.
• Knowledge of responsible AI principles and the ability to apply privacy, security, fairness, explainability, transparency, safety and human-oversight considerations to solution designs.
• Ability to evaluate AI use cases critically, identifying expected value, data dependencies, constraints, operational impacts and circumstances where AI should not be used.
• Experience creating architecture artefacts such as solution designs, integration views, data flows, decision records, standards and reusable patterns.
• Previous experience working within an organisation with established AI architecture governance, including design assurance, standards, guardrails and architectural decision-making.
• Experience identifying common needs across separate projects and translating them into reusable components, shared services or enterprise patterns.
• Ability to maintain a portfolio-level view of AI initiatives, manage architectural dependencies and challenge unnecessary duplication across delivery teams.
• Good stakeholder management skills, with the confidence to engage business leaders, architects, engineers, risk specialists and delivery teams.
• Clear written and verbal communication, including the ability to explain complex AI concepts in straightforward language to non-technical audiences.
• Curiosity and sound judgement, with a commitment to continuous learning in a rapidly changing technology and regulatory environment.

What we prefer you to have:

• Experience in insurance, reinsurance or another regulated financial-services environment.
• Knowledge of Microsoft AI services and tools, such as Azure AI Foundry, Azure OpenAI, Copilot Studio or Microsoft Fabric.
• Experience with Databricks, data platforms, semantic technologies, knowledge graphs or enterprise data governance.
• Familiarity with AI risk-management frameworks, model governance, threat modelling and emerging AI regulation.
• Experience supporting proofs of concept through to production adoption, including defining success measures and evaluating solution quality.
• Relevant cloud, architecture, data, security or AI certifications.

You will be eligible for a comprehensive and competitive benefits package which includes medical plans for you and your family, health and wellness programmes, retirement plans, tuition reimbursement, paid annual leave and much more.

In addition, you will be offered competitive target incentive compensation, with awards based on overall corporate and individual performance.