Top AI Jobs in Dublin

Embed with strategic enterprise customers to prototype, build, and productionize full‑stack generative AI and agentic applications. Advise on AI roadmaps, design scalable, secure solution architectures, codify repeatable patterns, and mentor teams to operationalize LLMOps/MLOps practices (evaluation, monitoring, serving, lifecycle).

Seeking a Senior Full-Stack Engineer to develop AI-driven web and mobile applications, focusing on scalable architectures and API integrations. Collaborate with product teams to translate features into technical solutions.

As an AI Product Manager, you will lead the application of AI in Health Information Systems, manage product portfolios, and ensure compliance with healthcare standards while delivering technology solutions that enhance patient care.

Lead and mentor a team of Applied Scientists and AI/ML Engineers to design, build, and deploy production-grade AI features for an AI-native CRM. Drive technical strategy for LLM operations, agentic workflows, RAG/vector-based solutions, and scalable data pipelines while partnering with platform teams to ensure performant, customer-centric ML systems.

Build and own end-to-end features for Chainguard's AI-enabled CI/CD and supply-chain security products. Design, implement, and iterate on integrations like hardened GitHub Actions, container tooling, and agentic AI features. Drive architectural decisions, collaborate with Product and front-end teams, and ship secure, production-ready developer tools.

Build, run, and improve AI-driven automations for FP&A, tax, and finance operations. Connect ERP, spend, equity, HRIS, and CRM systems to LLM-powered agents, maintain auditable workflows, and expand the finance team's AI capabilities while supporting forecasting, budgeting, reporting, and month-end close.

The Chief Data & AI Officer will lead the establishment of a company's data and AI infrastructure, ensuring reliable information capture, decision-making processes, AI system integration, and compliance with governance standards.

Lead design and implementation of CI/CD and AI-related product features, owning end-to-end delivery. Build and secure CI/CD systems, work with containers, registries, and Kubernetes, extend agentic AI into customer experiences, guide architecture, and collaborate closely with Product and front-end teams.

Build and ship secure, production-ready CI/CD and AI-integrated features end-to-end. Design, implement, and iterate on products (e.g., hardened GitHub Actions, agent features), work closely with Product and front-end teams, make architectural decisions, and extend Chainguard's agentic AI capabilities into customer-facing experiences.

Join a project evaluating AI chatbot voice mode by conducting voice conversations in Irish (en_IE), following predefined prompts and goals, then rating interactions and completing evaluations in English. Work remotely on personal smartphone and laptop, follow confidentiality and project guidelines, and be prepared for variable workloads and environment conditions.

Lead design, training, and production deployment of advanced ML models (including deep learning and graph architectures) for drug discovery. Own end-to-end model lifecycle, build scalable inference services and automated MLOps pipelines, validate models against scientific benchmarks, optimize for performance, and mentor teams to raise engineering excellence.

Lead the architecture and implementation of a production-grade generative AI media platform. Build reproducible, versioned pipelines, train LoRAs, integrate control techniques (ControlNet, IP-Adapter, inpainting), automate QC against product references, deploy internal tools, and partner with design to own the technical roadmap and enable creative teams.

Lead development and scaling of research-to-production ML infrastructure for reinforcement-learning-based industrial control. Build distributed training and experiment orchestration, optimize performance (vectorization, profiling), manage GPU capacity on Kubernetes/GCP, productionize models, document work, mentor peers, and act as liaison between Research and Production teams.

Lead end-to-end technical projects for a Voice AI CX platform: scope, plan, manage releases, align product to customer requirements, track metrics, ensure quality, and communicate status to clients and engineering.

Own SEO strategy and KPI progress for client accounts, build AI-supported workflows and automations, create repeatable SEO processes, lead client communications and reviews, and drive measurable visibility and business outcomes by combining AI tools and specialist expertise.

Manage multilingual data collection and Large Language Model evaluation projects, ensuring quality assurance and effective global team coordination.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Manage the GTM AI Engineering team overseeing automation, AI agent strategy, and integration with sales and marketing for revenue growth.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Partner with EMEA AI/ML teams to drive adoption of Arize's observability platform, manage accounts through onboarding and renewals, run workshops/QBRs, identify upsell opportunities, and coordinate technical resources to ensure customers achieve measurable AI outcomes.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Lead hands-on applied AI work: prototype demos, accelerate customer POC-to-production, perform technical onboarding, optimize distributed training and inference on GPU infrastructure, research and implement emerging ML techniques, and feed actionable product feedback while producing reusable assets and benchmarks.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.