Top AI Jobs in Dublin

Design polished, mobile-first interfaces and prototypes for BJAK's AI and financial products. Convert requirements into wireframes, flows and high-fidelity UI, evolve the design system, collaborate with PMs and engineers, iterate using user feedback and analytics, and ensure accessibility, responsiveness and visual consistency across devices.

Design, build, and deploy production-scale AI solutions (LLMs, RAG, agents, knowledge graphs) across Workday products. Integrate and optimize models, manage lifecycle, ensure performance, observability, security, and collaborate with product and ML teams to deliver user-focused AI features.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Design, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

Senior Director analyst providing thought leadership and actionable research on infrastructure and operations AI strategy. Produce insights, presentations, and client advisories; guide AI infrastructure, cloud adoption, integration, governance, and vendor selection. Lead research agenda, mentor analysts, collaborate cross-functionally (infrastructure, engineering, enterprise architecture, cybersecurity), support sales, and represent Gartner at events. Drive process improvements and influence senior stakeholders to align infrastructure and operations with business outcomes.

The candidate will design and implement software incorporating machine learning algorithms, optimize data pipelines, develop APIs, and provide mentorship to Junior Engineers.

The AI Support Engineer will solve complex customer issues, provide technical support for OpenAI products, and improve internal processes using AI and scripting.

Build and maintain scalable, resilient APIs and backend services for agentic AI use cases. Design contract-first APIs (OpenAPI/Swagger), ensure routing, auth, validation, transformation, and error handling. Improve observability, performance, and reliability; write tests and docs; own services end-to-end; mentor peers and collaborate across teams to enable AI-driven workflows.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Lead AI Business Analyst drives AI-driven transformation across global programs by identifying and implementing AI use cases, defining system-level specifications, leading pilots, designing AI-enabled workflows/dashboards, and partnering with IT and stakeholders to deliver measurable business value in insurance operations.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

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

Build and operate the internal AI platform used by 600+ developers: secure AI coding environments, AI-assisted CI and agentic AWS workflows. Own products end-to-end, improve developer experience, ensure reliability/observability/cost-awareness, participate in on-call, and capture reusable patterns and templates for broad adoption.

Build end-to-end AI-native product features across frontend, backend, and model integrations. Design and deploy agent workflows, integrate LLMs, memory, and external tools, and ensure real-time streaming, low-latency interactions, reliability, observability, and robust fallback/recovery. Collaborate with ML, backend, and product teams and iterate based on real-world usage.

Build and ship end-to-end AI features, shaping model behavior and surrounding systems. Design prompts, tools, memory, and agent workflows; convert model outputs into reliable behavior; debug across model, infra, orchestration, and UX; optimize latency, cost, and reliability; and develop evaluation frameworks to measure real-world performance.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Lead product marketing and go-to-market for Sia's AI product portfolio. Develop positioning, messaging, launch plans, field enablement assets (playbooks, demos, pitch materials), and coordinate cross-functional campaigns, events, and partner activity to drive adoption and awareness among technical and business audiences.

Partner with customers to design, prototype, and deploy AI-enabled cybersecurity workflows using OpenAI models and tooling. Lead discovery, scope pilots, build demos/proofs, advise on safe implementation patterns, create reusable field assets, and provide product feedback across AppSec, cloud security, SOC/IR, vulnerability management, and related domains.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

This role involves improving AI systems' reliability, designing monitoring systems, managing failover systems, and leading incident responses for critical AI services.

As an AI Product Manager at n8n, you'll develop AI-driven product experiences, coordinate with various teams, and innovate through user-centric design, focusing on AI trust and building.