Principal AI Product Engineer
Our client, a global Fortune 10 healthcare organisation, is hiring a Principal AI Product Engineer for an initial nine-month contract in Cork, Ireland. 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
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Design, develop and deploy production-ready AI products, taking solutions from early experimentation and prototyping through to scalable enterprise deployment.
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Build generative AI and machine learning applications, including LLM workflows, RAG systems, AI agents, predictive models and intelligent automation.
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Own the end-to-end technical architecture of AI products across models, data, APIs, infrastructure, security, observability and user experience.
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Create reusable AI platform components, frameworks and engineering patterns that accelerate the development and deployment of AI solutions across the company.
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Assess and integrate foundation models, AI platforms and emerging technologies, making informed decisions around build vs. buy, performance, cost, security and reliability.
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Develop evaluation, testing and monitoring frameworks to measure model performance, reliability, latency, safety, adoption and business value.
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Partner with Product, Engineering and business stakeholders to translate complex operational challenges into practical, high-impact AI solutions.
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Provide senior technical leadership across AI engineering, mentoring engineers, reviewing architectures and helping shape technical direction across multiple teams.
Skillset
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Extensive experience in software engineering, AI engineering or machine learning engineering, ideally operating at Principal, Staff or Senior Staff level.
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Strong hands-on engineering expertise with a proven track record of designing, building and operating large-scale production systems.
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Demonstrated experience taking AI and machine learning products from initial concept and prototyping through to production deployment and adoption.
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Practical experience building LLM and generative AI applications, including RAG, AI agents, tool calling, structured outputs, model evaluation and multi-model systems.
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Deep understanding of AI/ML architectures and the end-to-end model lifecycle, from data preparation and experimentation through to deployment, monitoring and optimisation.
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Experience working with MLOps/ModelOps, cloud platforms, APIs, data pipelines, observability and modern software development practices.
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Experience deploying AI within regulated, sensitive or high-stakes environments, with a strong understanding of security, privacy, governance, compliance and auditability.
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Proven ability to develop AI evaluation and testing frameworks covering accuracy, reliability, hallucination, latency, safety, cost and business impact.
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Strong product and commercial judgement, with the ability to identify high-value AI opportunities and translate them into practical technical solutions.
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Excellent communication and stakeholder management skills, with the ability to influence technical teams, product leaders and senior executives.
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