AI Portfolio Architect

Location : Hybrid role based in our City Centre offices

Hybrid working (part week at home, part in office), competitive salary and bonus, robust learning and development, defined contribution pension, and comprehensive wellbeing supports. Further details: Benefits (life‑ ).

At Irish Life, our purpose is to help people build better futures. Our values are built on integrity, doing the right thing, aiming high, putting customers at the heart of what we do, and working together in a supportive, collaborative environment.

The AI Portfolio Architect owns the enterprise‑grade AI strategy, architecture, and infrastructure for projects across Customer Solutions, ensuring all AI solutions align with ILG’s AI Governance Framework, the EU AI Act, GDPR, Central Bank expectations, EIOPA guidance, and emerging European standards.

You translate policy and regulatory requirements into practical architectural controls and technical patterns, and work closely with the AI Governance Lead, Portfolio and Solution Architects, Engineering, Risk, Data, EXO, European governance bodies, and business stakeholders to deliver safe, ethical, and scalable AI across Irish Life Group.

Strategic leadership & direction

• Define and champion the long‑term AI vision within Customer Solutions and across ILG.
• Develop and maintain an enterprise‑aligned roadmap for safe, scalable AI adoption.
• Shape AI capabilities across platforms, lifecycle maturity, governance, and engineering.
• Advise senior leaders on AI investments, platform evolution, and capital planning.
• Identify strategic AI opportunities and threats, informing direction and risk posture.
• Define and continually enhance enterprise AI architecture, reference patterns, and guardrails across analytics, ML, and generative AI.
• Translate AI governance requirements (EU AI Act, GDPR, DORA, Irish regulation, ILG rules) into actionable controls and standards.
• Ensure transparency, safety, explainability, auditability, and alignment with enterprise architecture.

Governance & regulatory compliance

• Implement frameworks defined by the AI Governance Lead, embedding controls into solution designs (e.g. bias mitigation, explainability, hallucination control, HITL, monitoring, lifecycle management).
• Provide technical risk assessments, architectural artefacts, and evidence for the Central AI Register, high‑risk classification, and audits.
• Ensure solutions meet European governance expectations and support escalations to EU committees where required.
• Identify technical risks in the CS AI domain and propose mitigation strategies to ensure stability, scalability, and performance.

Shape the AI use case portfolio

• Work with Product and Portfolio leadership to shape a prioritised AI opportunity pipeline.
• Assess feasibility, architectural risk, governance implications, and regulatory classification early in the lifecycle.
• Provide architectural leadership from discovery through design, delivery, and operationalisation.
• Develop the CS AI Roadmap aligned with business strategy.
• Lead the design of Azure AI and cloud‑native solutions, ensuring scalability, robustness, performance, and compliance with ILG security and risk standards.
• Promote mature MLOps/LLMOps operating models and integrated AI lifecycle controls.
• Engage proactively with business leaders, vendors, and architects to understand needs and communicate possibilities and constraints.

Governance forums & collaboration

• Be a standing member of the Customer Solutions Design Authority and represent the portfolio in ILG Enterprise Architecture forums.
• Represent AI portfolio interests at ILG Architecture and AI Governance Boards, working closely with Strategy & Architecture and Risk leads.
• Ensure all AI designs meet enterprise architecture principles, security requirements, and regulatory obligations.
• Partner with AI Governance, Risk, Legal, Data, EXO, Engineering, and operations to ensure safe, compliant delivery of AI.
• Translate complex regulatory and technical requirements into clear, business‑friendly guidance.
• Support uplift of AI literacy, governance capability, and good architectural practice across CS and ILG.
• Ensure commercial awareness and consideration of total cost of ownership in design decisions.

Continuous improvement & innovation

• Stay ahead of emerging AI regulations, industry standards, model safety techniques, and architectural innovations.
• Identify opportunities to improve AI governance maturity, accelerators, reusable patterns, and documentation.

Key skills and Capabilities

• Excellent collaboration skills across IS, especially with data science, engineering, and AI governance teams.
• Ability to influence and support senior IS and business leaders, ensuring AI initiatives align with strategic objectives and responsible AI principles.
• Strong experience delivering complex AI and data‑driven solutions in large enterprises and leading architectural direction for analytics, ML, and enterprise AI.
• Good knowledge of application engineering plus experience with MLOps, AI lifecycle management, and agile delivery.
• Ability to produce high‑quality architecture and design artefacts (AI reference architectures, data flows, governance artefacts) and present to senior stakeholders.
• Strong problem‑solving and decision‑making abilities, assessing AI‑related risks, trade‑offs, and ethical considerations.
• Experience designing AI‑enabled solutions using ML, generative AI, analytics, and automation to drive business value.
• Experience with data integration patterns, AI security best practice, model governance frameworks, and handling sensitive data securely.
• Versatile experience across on‑prem, private, hybrid, and public cloud AI services.
• Knowledge of modern AI patterns and technologies (e.g. vector databases, LLM orchestration, prompt engineering, model evaluation).
• Experience with Microsoft AI ecosystem (Azure OpenAI, Cognitive Services, Fabric, Power Platform).
• Scripting and automation experience (e.g. Python, PowerShell) including integration with APIs, AI pipelines, and DevOps/MLOps tooling.
• Understanding of data and model infrastructure (feature stores, model registries, inference optimisation, scalable APIs).
• Ability to align AI non‑functional requirements (fairness, interpretability, performance, latency, scalability, cost) with business strategy and risk appetite.
• Strong understanding of emerging AI regulations, especially the EU AI Act, and ability to translate these into practical technical and architectural requirements.
• Ability to embed regulatory compliance into architecture and delivery, ensuring logging, monitoring, robustness, documentation, and clear team responsibilities.
• Minimum 7 years’ experience in technical design and delivery of strategic AI, data, or analytics solutions on enterprise‑scale platforms.
• Strong understanding of modern AI integration and orchestration services (e.g. Azure Machine Learning, Azure OpenAI, Cognitive Services, Logic Apps, Azure Functions, enterprise API layers and RAG).
• Advanced knowledge of AI lifecycle automation and MLOps, including model evaluation, deployment, and AI risk controls.
• Experience in AI security, scalability, observability, and performance optimisation in highly regulated environments.
• Strong grasp of enterprise architecture best practice and AI‑specific governance standards.
• Familiarity with agile and cross‑functional delivery.
• Strong stakeholder management and communication skills, able to demystify complex AI concepts and risks.
• Practical experience integrating regulatory and compliance frameworks (including EU AI Act) into AI delivery and supporting audits and conformity assessments.
• Sound understanding of application, infrastructure, and security frameworks.
• Deep understanding of Microsoft Azure AI and data technologies (e.g. Azure ML, Azure OpenAI, Cognitive Search, Databricks on Azure, Fabric).
• Experience with end‑to‑end AI solution architectures across IaaS, PaaS, and SaaS.
• Financial services experience, ideally life assurance.
• Relevant certifications (e.g. Azure Solutions Architect Expert, Azure AI Engineer Associate).
• Experience contributing to AI assurance frameworks (model cards, documentation templates, transparency artefacts, audit‑ready controls).

About us

Irish Life is one of Ireland’s largest financial institutions with over 1.5 million customers across life insurance, pensions, investments, and health insurance. We are a subsidiary of Great‑West Lifeco and part of the Power Financial Corporation group.

We invest heavily in developing our people and maintaining high professional standards, which keeps us at the forefront of our industry.

The company may draw up a shortlist as part of the selection process. Where agency assistance is required, the Irish Life Recruitment Team will engage directly; unsolicited CVs from agencies will not be accepted.

Irish Life is proud to be an equal opportunities employer, committed to inclusion, diversity, and enabling people to bring their whole selves to work. xcfaprz If you require any accommodation during the recruitment process, please contact

ILFS supports Equal Opportunity and is regulated by the Central Bank of Ireland.