Top AI Jobs in Dublin

Lead enterprise product strategy and transformation across Wolters Kluwer. The role focuses on scaling AI-enabled and agentic product development, coaching product leaders, improving operating models, leading cross-functional lighthouse initiatives, and establishing reusable tools, practices, metrics, and governance. Success requires influencing senior stakeholders without formal authority and driving measurable improvements in product discovery, delivery, launch, and outcomes across a global software portfolio.

Drive new-logo acquisition for Axway’s AI Gateway and Amplify portfolio across large enterprise and regulated-industry accounts. Responsibilities include strategic prospecting, executive engagement, pipeline creation, complex enterprise sales, business-case development, technical validation, negotiation, and contract closure. The role focuses on API security, governance, AI adoption, enterprise integration, and digital transformation, while collaborating with presales, product, marketing, partners, and executives.

Leads a team of AI Business Process Digital Solution Specialists and Engineers focused on selling Microsoft Dynamics 365, Power Platform, and Copilot solutions. Responsibilities include sales strategy, pipeline and forecast management, complex deal coaching, customer and executive engagement, partner strategy, team hiring and development, performance management, and adoption of AI-driven business process solutions across German-speaking markets.

Leads CEL’s enterprise AI adoption by developing the AI roadmap, identifying and scaling use cases, integrating AI with ERP, CAD/PLM, CRM, Microsoft 365, and other systems, and establishing responsible AI governance. The role partners with business, IT, vendors, and external providers; develops adoption metrics; trains employees; manages change; and supports AI-enabled engineering, predictive maintenance, analytics, and intelligent infrastructure initiatives.

Leads the design, development, deployment, and evaluation of machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, and partners with product, engineering, analytics, and business teams. Mentors data scientists and AI engineers, presents technical recommendations to leadership, supports hiring, and shapes the organization’s long-term technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, measures business impact, partners with cross-functional stakeholders, presents findings to leadership, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model representations, measures business impact, and partners with cross-functional stakeholders. Mentors data scientists and AI engineers, presents recommendations to leadership, contributes to hiring, and helps shape the organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies embeddings and foundation models, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. Contributes to hiring, capability development, and the long-term technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendations, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners across functions, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the AI organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions for forecasting, recommendations, propensity modeling, fraud detection, and customer analytics. Defines modeling and experimentation strategies, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, and mentors data scientists and AI engineers. The role also contributes to technical direction, hiring, and capability development.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the long-term technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks, metrics, and technical direction while partnering with business, product, engineering, and analytics teams. Presents insights to senior stakeholders, mentors data scientists and AI engineers, and drives projects from problem definition through measurable business impact and production deployment.

Lead machine learning and data science initiatives from problem definition through production deployment and business impact measurement. Develop predictive models, recommendation systems, forecasting, fraud detection, and customer analytics solutions using modern machine learning and foundation-model techniques. Establish experimentation and evaluation frameworks, partner with cross-functional stakeholders, present technical recommendations, mentor data scientists and AI engineers, and shape the organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendations, fraud detection, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, drives projects from conception through production, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. Contributes to hiring, capability development, and the organization’s long-term technical direction.

Leads the design, development, deployment, and evaluation of advanced machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies embeddings and foundation-model techniques, measures business impact, and partners with business, product, engineering, and analytics teams. Mentors data scientists and AI engineers, influences technical direction, presents findings to leadership, and contributes to hiring and capability development.

Provides legal counsel for SaaS products, commercial contracts, privacy, data protection, and global AI regulation. Advises Sales and Engineering during contracting and product development, negotiates data protection agreements, conducts privacy and risk assessments, develops compliance programs, monitors AI legislation, works with regulators, trains employees, and mentors a junior legal associate.

Manages science and technology initiatives for sustainable industrial fisheries. Leads multidisciplinary projects involving electronic monitoring, AI, machine learning, computer vision, data systems, hardware, software deployment, and seafood traceability. Oversees vendors, contractors, budgets, procurements, technical assessments, and deployment of systems in remote environments. Translates technical concepts for diverse stakeholders and supports technology evaluation, scaling, and conservation strategy. The role may require domestic and international travel of 25% or more.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Provide privacy and AI legal guidance across EMEA, including negotiating data processing agreements, developing global privacy programs, preparing impact assessments, monitoring privacy and AI regulations, and supporting EU AI Act and UK AI governance compliance. Partner with product, engineering, security, commercial, sales, and compliance teams on AI system classification, risk assessments, governance controls, transparency, accountability, and human oversight.

Drive enterprise sales of Microsoft security solutions across assigned accounts and territories. Identify cybersecurity needs, recommend cloud-based solutions, lead customer and partner engagements, manage stakeholder mapping, and coordinate cross-functional teams to close opportunities. Grow security consumption and licensing through digital selling, cross-selling, up-selling, networking, and social selling. The role requires fluent English and Arabic plus technology-related sales or account management experience.

Lead Chainguard’s European government affairs and public policy strategy across the UK and Europe. Engage regulators, governments, standards bodies, and industry coalitions; develop policy positions and consultation responses; translate cybersecurity regulations into product, positioning, and customer implications; and establish a scalable policy function. The role requires senior stakeholder engagement, technical policy communication, frequent regional travel, and eventual team-building responsibility.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Leads enterprise technology strategy, delivery, and transformation across Finance, FinTech, Legal, and Risk. Oversees product platforms, Agile and DevOps adoption, AI and data initiatives, digital transformation, change management, vendor partnerships, governance, and technology operations. Partners with executive stakeholders to align global priorities, integrate platforms, manage dependencies, and deliver scalable, secure, value-driven outcomes across a federated enterprise technology organization.

Lead Dotmatics’ AI governance program by developing frameworks, risk tiering, use-case registries, policies, controls, and reporting aligned with regulations and standards. Coordinate the AI Governance Council and Siemens consortium, assess AI risks across product and business functions, embed controls into the SDLC, respond to customer due diligence, and deliver training. The role requires executive communication, cross-functional influence, technical understanding of AI/ML systems, and extensive information security, technology risk, compliance, and regulated-industry experience.

Supports People & Values operations by improving employee lifecycle processes, administering HR systems, maintaining documentation and policies, implementing automation, and managing contingent workforce contracts. The role partners with Talent Acquisition, Legal, Finance, and internal stakeholders to improve onboarding, ensure compliance, maintain data integrity, and deliver scalable employee experiences.