AI Transformation Specialist

Alldus International Consulting Ltd; Cork; On-site; EUR 100,000 - 150,000; Full time

Job summary

Alldus International Consulting Ltd connects with a global Fortune 10 healthcare organisation to hire an AI Transformation Specialist for an initial nine-month contract in Ireland. The role leads the design, development and scaling of AI-powered products, moving ambitious AI use cases from experimentation to production.

You will own end-to-end AI architectures, collaborate with product and engineering teams, and mentor engineers while shaping technical direction across multiple teams.

Qualifications

• Extensive software/AI engineering experience at principal to senior levels.
• Proven track record delivering large-scale production AI systems.
• Experience deploying LLM and generative AI applications (RAG, agents).

Responsibilities

• Design, develop and deploy production-ready AI products from prototype to enterprise deployment.
• Build generative AI applications including LLM workflows and RAG systems.
• Own end-to-end architecture across models, data, APIs, infra, security, and UX.
• Create reusable AI platform components and engineering patterns.
• Assess foundation models and emerging tech, balancing build vs buy.
• Develop evaluation and monitoring frameworks for model performance and value.
• Partner with product and stakeholders to translate challenges into AI solutions.
• Provide senior technical leadership across AI engineering and mentoring teams.

Skills

AI Architecture

MLOps

Cloud Platforms

LLM / Generative AI

Production Systems

Model Evaluation

Security & Governance

Stakeholder Communication

Leadership

Job description

Our client, a global Fortune 10 healthcare organisation, is hiring a AI Transformation Specialistfor an initial nine-month contract inIreland. The successful candidate will be responsible for designing, building and scaling AI-powered products, transforming ambitious AI use cases from early-stage experimentation into robust, production-ready systems.

Responsibilities

• Design, develop and deploy production-ready AI products, taking solutions from early experimentation and prototyping through to scalable enterprise deployment.
• Build generative AI and machine learning applications, including LLM workflows, RAG systems, AI agents, predictive models and intelligent automation.
• Own the end-to-end technical architecture of AI products across models, data, APIs, infrastructure, security, observability and user experience.
• Create reusable AI platform components, frameworks and engineering patterns that accelerate the development and deployment of AI solutions across the company.
• Assess and integrate foundation models, AI platforms and emerging technologies, making informed decisions around build vs. buy, performance, cost, security and reliability.
• Develop evaluation, testing and monitoring frameworks to measure model performance, reliability, latency, safety, adoption and business value.
• Partner with Product, Engineering and business stakeholders to translate complex operational challenges into practical, high-impact AI solutions.
• Provide senior technical leadership across AI engineering, mentoring engineers, reviewing architectures and helping shape technical direction across multiple teams.

Skillset

• Extensive experience in software engineering, AI engineering or machine learning engineering, ideally operating at Principal, Staff or Senior Staff level.
• Strong hands-on engineering expertise with a proven track record of designing, building and operating large-scale production systems.
• Demonstrated experience taking AI and machine learning products from initial concept and prototyping through to production deployment and adoption.
• Practical experience building LLM and generative AI applications, including RAG, AI agents, tool calling, structured outputs, model evaluation and multi-model systems.
• Deep understanding of AI/ML architectures and the end-to-end model lifecycle, from data preparation and experimentation through to deployment, monitoring and optimisation.
• Experience working with MLOps/ModelOps, cloud platforms, APIs, data pipelines, observability and modern software development practices.
• Experience deploying AI within regulated, sensitive or high-stakes environments, with a strong understanding of security, privacy, governance, compliance and auditability.
• Proven ability to develop AI evaluation and testing frameworks covering accuracy, reliability, hallucination, latency, safety, cost and business impact.
• Strong product and commercial judgement, with the ability to identify high-value AI opportunities and translate them into practical technical solutions.
• Excellent communication and stakeholder management skills, with the ability to influence technical teams, product leaders and senior executives.