AI & Data Science Team Lead / Architect
Lead the design and deployment of agentic AI systems and enterprise copilots using AWS Bedrock, SageMaker, and Microsoft Copilot Studio, while mentoring a team of data scientists and AI engineers.
- Compensation
- Not disclosed
- Location
- Dublin, Ireland
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Contract
- Experience
- 1+ years
- Category
- Data science
- Posted
Skills
Nice to have
- Experience designing or deploying agentic or multi-agent AI systems.
- Prior experience within banking or the broader financial services industry.
- Deep expertise in areas such as NLP, GenAI, deep learning, or decision intelligence.
- Practical experience with MLOps / LLMOps practices and tooling.
- Cloud certifications (Azure or AWS) or deep practical cloud experience.
- Experience building and deploying GenAI applications at scale.
Full description
This is a contract position.
Ireland & UK-based candidates (travel to Ireland).
Role Overview
As the AI & Data Science Team Lead, you will spearhead the design, development, and deployment of agentic AI solutions and advanced machine learning systems that solve complex business and customer problems at scale.
This role combines deep technical leadership with AI architecture ownership. You will guide the adoption of cloud platforms, such as Amazon Bedrock, Bedrock Agents, SageMaker and Microsoft Copilot Studio, to deliver secure, explainable, and production-ready AI capabilities across the organisation.
Spanning strategy, discovery, architecture, and delivery, you will shape how AI agents, copilots, and decisioning systems are designed, orchestrated, deployed, and governed, while mentoring a high-performing team of data scientists and AI engineers.
You will be a senior member of the AI & Data Science team within the Enterprise Data & Analytics Division, working at the intersection of Data Science, AI Engineering, Enterprise Architecture, Product and Business Teams. You will play a key role in establishing AI platform standards, reusable agent frameworks, and responsible AI practices, helping to embed AI-driven decision making across the organisation in a safe and scalable way.
Key Responsibilities
AI Leadership & Agentic Systems
- Lead Agentic AI Design: Provide technical leadership on the design and implementation of agentic AI systems, including multi-agent workflows, tool-using agents, orchestration patterns, and human-in-the-loop designs.
- Drive Enterprise Copilots: Lead the development of enterprise copilots and AI assistants using Microsoft Copilot Studio, aligning them to real business workflows and measurable outcomes.
- Establish Frameworks: Define best practices for prompt engineering, memory strategies, tool calling, evaluation, and agent reliability.
AI Architecture & Platform Design
- Own End-to-End Architecture: Drive AI solution architecture from initial experimentation through to full production using AWS Bedrock, SageMaker, and supporting AWS services.
- Collaborate on Infrastructure: Partner with cloud, data, and security architects to design secure, scalable, and compliant AI platforms, including model lifecycle management and environment separation.
- Standardise Assets: Drive the development of reusable AI assets, agent templates, and reference architectures to accelerate delivery across multiple teams.