Top AI Jobs in Dublin

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Serve as a technical-strategic partner for AI Decisioning customers, leading use-case delivery from discovery through go-live and expansion. Collaborate with engineers, executives, marketers, and IT stakeholders to define requirements, explore customer data, recommend marketing improvements, manage project risks, and develop delivery best practices. The role also contributes to AI Decisioning product strategy and requires customer-facing consulting, strong communication, and 10–25% travel.

Own end-to-end product marketing for Operator, Fin’s AI agent for customer operations. Develop category-defining narratives, positioning, ICP and messaging; lead launches and go-to-market initiatives; create sales enablement, competitive positioning, web content, demos and other PMM assets. Partner with product, marketing, sales and leadership, conduct customer research, translate technical capabilities into clear value, and maintain messaging systems supporting Fin’s AI-first approach.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Own product features end-to-end, including architecture, integrations, technical specifications, deployment, testing, and production reliability. Use AI agents as the primary development tool, delegate implementation, critically review generated code, and ensure financial transaction reliability. Work independently as an individual contributor while helping evolve the company’s AI-first development process.

Lead multiple teams building the Guidewire Cloud Platform and Jutro Digital Platform (JDP). Drive technical excellence across frontend (React, Module Federation) and backend (Java/Kotlin, Spring Boot) microservices on AWS and Kubernetes, champion AI-assisted Spec-Driven Development, manage delivery, hiring, incident response, and mentor engineers to improve quality and velocity.

Manage enterprise customer accounts to drive product adoption, value realization, satisfaction, retention, renewals, and expansion. Build success plans, monitor customer health, conduct business reviews, manage escalations, and coordinate cross-functional teams. Serve as a trusted advisor to business and technical stakeholders while advocating for customer needs. The role requires fluent English and German and supports software, SaaS, cybersecurity, and data management customers.

Develop backend software and agentic AI solutions using Java, Spring Boot, microservices, and REST APIs. Design scalable systems, integrate relational and distributed data stores, and deploy across AWS and Azure. Implement automated testing, CI/CD, observability, and production readiness practices. Collaborate across teams and stakeholders, deliver complex software solutions, and mentor engineers. The role is hybrid in Dublin, Ireland, with 9 AM–6 PM working hours.

Leads ICON’s enterprise AI engineering platform, multi-agent framework, and agent services. Responsibilities include platform development, CI/CD, testing, deployment governance, monitoring, incident management, security, compliance, and responsible AI. The role manages and mentors engineering teams, oversees delivery across AI programs, supports technology roadmaps, and partners with stakeholders to deliver secure, scalable, reliable production AI systems.

Drive enterprise solution sales for Microsoft Modern Work, AI, Copilot, and cloud offerings to French-speaking enterprise or public-sector customers. Identify business needs, develop tailored solutions, build stakeholder relationships, lead value-selling conversations, coordinate internal teams and partners, and close new business. The role includes account planning, forecasting, competitive analysis, cross-selling, up-selling, and end-to-end sales execution.

Design, deploy, and operate production AI agents and generative AI solutions using Azure OpenAI, Snowflake, Databricks, retrieval, semantic models, and tool orchestration. Build reliable data workflows, governance, security, monitoring, evaluation, and responsible AI controls for sensitive healthcare data. Integrate AI systems with enterprise applications and APIs, troubleshoot performance and retrieval issues, and collaborate with technical and business stakeholders to deliver compliant, scalable solutions.

Partner with mid-market customers to drive revenue transformation using Gong’s AI Operating System. Design AI-driven workflows, lead adoption and change management, quantify ROI, and manage renewals and expansion. The role requires executive stakeholder engagement, cross-functional collaboration, and ownership of customer activation, value realization, retention, and revenue growth.

Partner with enterprise customers and senior GTM stakeholders to drive revenue transformation using Gong’s AI Operating System. Architect AI-enabled workflows, lead adoption and change management, quantify ROI, and deliver measurable customer outcomes. Own renewal strategy and expansion opportunities while collaborating cross-functionally with Sales, Product, Support, Marketing, and executives. Success is measured through activation, adoption, value realization, retention, expansion, and revenue impact.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.

Designs, develops, tests, and deploys intelligent business solutions using Microsoft Copilot Studio, Microsoft 365 Copilot, and Power Platform. Integrates enterprise systems through Microsoft Graph, APIs, Azure services, and custom connectors. Works directly with clients to translate business needs into secure, scalable solutions, while supporting governance, testing, optimization, documentation, demos, workshops, and enterprise rollouts.

Own the backend and agent systems powering LLM products, including multi-turn conversations, tool calling, RAG, state management, evaluations, monitoring, and production reliability. Diagnose failures across models, knowledge systems, tools, and infrastructure; establish regression testing and quality measurement; and guide product and technical decisions. The role requires shipping and improving LLM features at scale, strong backend engineering, disciplined evaluation practices, and preferably Web3 experience.

Leads Grant Thornton’s internal AI product strategy, portfolio governance, roadmap, delivery oversight, adoption, and continuous improvement. The role translates senior leadership priorities into governed, scalable AI products, accelerators, and workflow tools. Responsibilities include leading multidisciplinary teams, managing stakeholders, evaluating build-versus-buy decisions, overseeing risks and investment, supporting responsible AI practices, developing reusable intellectual property, and coaching team members. The position is hybrid, typically requiring two days weekly in the Dublin or Belfast office.

Own the quality strategy and end-to-end testing pipeline for an AI-generated product handling real-money transactions. Build automated UI, browser, mobile, pre-merge, nightly, release, and production testing gates; integrate testing with CI/CD; evaluate external tools; and improve reliability of critical financial flows. The role partners with engineering and DevOps, uses AI coding agents daily, and drives quality initiatives as an autonomous individual contributor.

Lead AI and data-science research for toxicologic and translational pathology. Responsibilities include curating large pathology datasets, designing foundation-model and deep-learning experiments, building benchmarks, validating models, developing reproducible pipelines, and supporting biomarker discovery and tissue-based analyses. The role collaborates with pathologists, AI researchers, engineers, and product teams to produce rigorous evidence, publications, and product-ready capabilities.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Lead a team of senior support engineers handling complex technical escalations, production reliability, incident management, workload monitoring, alerting, and 24x7 coverage for strategic enterprise customers. Drive automation-first tooling, improve support processes, collaborate with Product and Engineering, influence product roadmaps, represent Support Engineering with customers, and contribute to hiring, strategy, and team culture.

Leads enterprise Microsoft 365 transformation initiatives focused on SharePoint Online, Power Platform, Copilot, AI agents, automation, security, compliance, and governance. Architects and implements collaboration solutions, migrates legacy platforms, configures Purview and related controls, and develops AI governance strategies. Provides technical leadership, client engagement, workshops, training, and ongoing support while coordinating project risks and dependencies. Requires availability during Eastern Time business hours and deep Microsoft 365, security, programming, database, and cross-tenant migration expertise.

Build and maintain PHP and Laravel backend services and APIs for a major product release. Own features from design through deployment and monitoring, integrate agentic AI workflows and LLM-based tooling, optimize performance and reliability, improve security, and mentor engineers. Collaborate independently with a cross-functional team on ambiguous technical challenges while delivering production-ready software.