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
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