AI/ML Solutions Lead

Job Role: AI/ML Solutions Lead

Location: Dublin

Career Level: 7 - Manager

Travel Required: Up to 30%

WHY THIS ROLE

Enterprise AI is maturing fast. Clients are moving past proof-of-concept and into production systems that need to be reliable, scalable, and genuinely useful. Accenture's AI and Data practice in Ireland is at the centre of that work, and this role sits within the delivery function making it happen.

For an engineer who wants client exposure, technical breadth, and the scope to build something worth building, this is a strong position.

THE ROLE

The AI/ML Solutions Lead owns the technical delivery of AI solutions for some of Ireland's most complex organisations. The scope is broad: agentic systems, LLM-powered applications, foundational model development, fine tuning, and production ML across computer vision, time series, and other disciplines.

The role carries team leadership responsibility. You will manage a group of AI/ML engineers, set technical standards, and be accountable for delivery quality across engagements.

Beyond delivery, this role contributes to how the practice builds AI. That includes shaping methodology, developing reusable assets, and supporting business development where relevant.

WHAT YOU WILL DO

• Lead AI solution delivery across the full lifecycle, from architecture and build through to production deployment, across financial services, public sector, and industry clients
• Design and build multi agent AI systems using established frameworks or custom orchestration where the problem requires it
• Architect LLM powered applications: RAG pipelines, tool augmented agents, and memory enabled systems grounded in enterprise data
• Build production grade agentic infrastructure: state management, task decomposition, human in the loop controls, guardrails, and observability
• Manage and develop a team of AI/ML engineers, maintaining clear technical standards and supporting individual growth
• Define safety boundaries, escalation logic, and audit mechanisms for autonomous systems in regulated environments
• Work with AI Solution Architects and Data Architects to translate client requirements into deployable technical plans
• Contribute to practice development: frameworks, accelerators, and reusable solution patterns
• Support business development through proposal input, client demonstrations, and building senior relationships over time

WHAT WE ARE LOOKING FOR:

• Seven or more years of hands on AI/ML engineering experience, with at least three years in a technical leadership or management position
• Solid grasp of foundational AI/ML model architectures, including transformer models and how they compare to and interact with diffusion based approaches
• Production delivery experience across at least one of: agentic systems, LLM applications, computer vision, or time series forecasting
• Working knowledge of LLM application development: prompt engineering, RAG, fine tuning, and evaluation
• Familiarity with agentic frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or CrewAI. Candidates who built custom orchestration before these tools existed are equally welcome
• Python proficiency with strong ML engineering fundamentals. PyTorch is required; ONNX and BentoML experience is a meaningful advantage for model serving and deployment
• Practical MLOps experience: CI/CD for ML, model monitoring, feature stores, and experiment tracking
• Cloud platform experience across Azure (Azure AI Foundry, Azure ML), AWS (Bedrock, SageMaker), or GCP (Vertex AI)
• Ability to communicate technical decisions clearly to both engineering teams and senior client stakeholders
• A track record of building and developing engineering teams

BONUS POINTS:

• Experience designing human in the loop workflows and escalation logic for autonomous AI systems
• Familiarity with responsible AI frameworks, bias detection, and model governance in agentic contexts
• Open source contributions, custom framework development, or published work on agentic systems
• Experience in regulated industries where autonomous AI carries additional compliance and oversight requirements

KEY SKILLS:

Python PyTorch ONNX Agentic AI LLMs Computer Vision MLOps Azure ML Responsible AI