Top AI Jobs in Dublin

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Lead client engagements to design and implement Microsoft Purview and Microsoft 365 Copilot governance and readiness. Deploy sensitivity labels, DLP, retention, eDiscovery, audit controls, run stakeholder workshops, translate requirements into business outcomes, and support secure AI workplace adoption across Microsoft 365 services.

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.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Own and improve Primer's GTM intelligence: maintain dashboards and semantic models, train BI/LLM models (Omni/Claude), surface pipeline/account signals, ensure correct Salesforce modeling, build revenue-driving models and GTM AI workflows, partner with data engineering and RevOps, drive adoption, and promote self-serve data literacy.

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.

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.

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.

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.

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.

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.