AI Architecture & Engineering Lead

DB Recruitment; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

DB Recruitment in Dublin is seeking an AI Architecture & Engineering Lead to design enterprise-grade AI solutions, including autonomous agents and GenAI. This hands-on role blends engineering leadership with consulting and client delivery, carrying solutions from concept through production.

You will set technical standards, lead workshops with executives, govern data and security, and ensure scalable, ethical AI deployments across AWS/Azure/GCP.

Qualifications

• Advanced design and deployment of production-ready AI solutions.
• Experience in orchestrating autonomous AI agents with planning and tool use.
• Leadership in AI frameworks and governance across platforms.

Responsibilities

• Shape AI architecture and policies for enterprise use and governance.
• Lead executive workshops to identify AI use cases and ethical adoption roadmaps.
• Turn business challenges into actionable technical plans with security compliance.
• Drive cross-competency AI training and platform capability development.
• Architect multi-step autonomous agent systems using LLMs and vector stores.
• Set standards and QA for AI and MLOps workflows.
• Recommend tools and platforms based on performance and cost.
• Ensure AI strategies follow ethical principles and minimize bias.

Skills

AI architecture

LLM workflows

Autonomous agents

Cloud platforms

MLOps

Tools

Flowise

LlamaIndex

Pinecone

Weaviate

Milvus

PyTorch

TensorFlow

Hugging Face

Job description

We have an exciting new AI Architecture & Engineering Lead with a top multinational in Dublin

They are looking for a hands‑on architecture & engineering lead, you will design enterprise-grade AI solutions - Agentic & Gen-AI.

This role blends deep hands‑on engineering, consulting judgment, and client‑facing delivery ownership. You will carry solutions from concept through production and enable clients to sustainably operate and evolve their AI capabilities.

Responsibilities

• Shape technical policies and architecture for AI and autonomous systems to strengthen competitive advantage.
• Lead executive workshops to identify high‑value AI use cases, assess readiness, and create ethical adoption roadmaps. Collaborate with stakeholders to align architecture with strategy.
• Turn business challenges into actionable technical plans compliant with data governance and security standards.
• Integrate AI practice across competencies by leading training and platform expertise development.
• Architect multi‑step autonomous agent systems using LLMs, vector databases, and orchestration frameworks with a focus on scale and reliability.
• Set technical standards and QA processes for AI and MLOps workflows.
• Recommend AI tools and platforms based on performance and cost.
• Ensure AI strategies and systems follow ethical principles and minimize risks like bias and privacy issues.

Your experience:

• Advanced skills in designing and deploying production‑ready AI solutions and Large Language Model (LLM) workflows.
• Proven experience in building and orchestrating autonomous AI agents encompassing reasoning, tool utilization, and multi‑step planning.
• Expert proficiency in leading AI frameworks.
• Comprehensive knowledge of cloud computing platforms such as AWS, Azure, or GCP, and related MLOps tools.
• Preferred experience with low‑code/no‑code AI agent builder platforms (e.g., Flowise, LlamaIndex).
• Comprehensive AI skills across Agentic AI, Document Intelligence, Time Series, and multimodal GenAI.
• Usage of PyTorch/TensorFlow and Hugging Face; integration of ML into enterprise pipelines.
• Design of organization‑level evaluation and scoring frameworks (text, vision, multimodal) with release gates (R/A/G).
• Governance: alignment to EU AI Act; model/prompt/data versioning; audit logs; risk management. Exposure on control plane solutions in the market
• LLM Strategy: evaluate and standardize across providers (OpenAI, Anthropic, Google Gemini, Mistral, Llama) and vector platforms (Pinecone/Weaviate/Milvus).
• Cloud: multi‑cloud and hybrid architecture across AWS, Azure, and GCP; reliability/SLOs; cost/tokens governance.