Top AI Jobs in Dublin

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Build and operate RenaissanceRe’s internal AI platform, including reusable tools, cloud-native deployments, enterprise integrations, monitoring, governance, testing, and responsible-AI controls. Develop AI agents, RAG frameworks, tool-calling workflows, and scalable services using Python, AWS, Docker, and orchestration frameworks. Support security, privacy, compliance, performance, reliability, and cost optimization while partnering with product, data, platform, and engineering teams to accelerate AI adoption.

Lead product vision and roadmap for agentic AI solutions, own the backlog, translate business needs into user stories, partner with data scientists and engineers, manage Agile delivery cycles, ensure responsible AI practices, and monitor model performance and continuous improvement.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Own the vision, strategy, roadmap, and impact for a major area of Fin’s AI platform or agent. Collaborate with machine learning scientists, engineers, researchers, designers, and cross-functional teams to turn advanced AI capabilities into valuable products. Lead discovery, experimentation, evaluation, production launches, metric definition, iteration, customer insight, alignment, and adoption while prioritizing safety, reliability, and customer outcomes.

Lead research and advisory on application security for enterprise applications (ERP/CRM). Produce thought leadership, client-facing insights, presentations, market analysis, and support sales. Mentor analysts, drive research agenda, improve processes, and advise CIOs on security strategy, vendor evaluation, metrics, and vulnerability testing across major vendors (SAP, Salesforce, Workday, Oracle).

The Senior Software Engineer will lead application modernization initiatives, collaborate with cross-functional teams, develop tools, and provide strategic insights to improve customer engagement and product roadmap.

Build and operate Typeform’s internal AI Operations capability for R&D. Identify and prioritize AI opportunities, discover workflows, design and deliver AI-native solutions, and manage their lifecycle after launch. Responsibilities include improving enterprise AI tools, coordinating access and governance, evaluating reliability and security, supporting automations and agents, measuring adoption and value, and partnering with Product, Engineering, IT, InfoSec, Finance, and other teams.

Lead discovery, rapid prototyping, and deployment of production-ready AI solutions for supply chain and manufacturing. Build Python-based RAG pipelines, semantic search, multi-agent workflows, data integrations, and enterprise platform connections. Engage frontline operations, translate business needs into technical requirements, manage agile delivery, and ensure prototypes are scalable and transferable to core engineering teams. Work across SAP, MES, shop-floor platforms, databases, telemetry, and unstructured data while collaborating with security, data, and architecture teams.

The Senior Applied AI/ML Scientist will build and ship LLM-powered features, drive quality in evaluation, improve retrieval systems, and lead technical discussions with a focus on AI and engineering collaboration.

Coordinates the AI Accountability Network’s newsletters, training programs, grants, fellowships, payments, events, communications, and community initiatives. Manages editorial workflows, contractors, applications, logistics, websites, listservs, dashboards, metrics, and stakeholder communications. Supports grant administration, funder reporting, travel, curriculum development, and website publishing while improving processes and tracking program impact.

Build and refine AI-powered prototypes for supply chain and manufacturing operations. Engage with factory and warehouse teams, translate operational needs into software requirements, develop Python-based RAG and agentic systems, integrate APIs and data sources, and iterate prototypes based on frontline feedback. The role involves SQL and document data preparation, agile collaboration, occasional manufacturing-site travel, and progressive adoption of enterprise AI frameworks and production engineering practices.

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

Join Welo Data’s French AI Trainers Network as a flexible contributor supporting annotation, evaluation, and prompt creation projects. Contributors may label text, images, or audio; assess search results, advertisements, and chatbot responses; create prompts for large language models; and ensure cultural and linguistic accuracy. This is a talent community rather than an active opening, with project details and compensation provided when assignments become available.

Lead the end-to-end product experience across acquisition, onboarding, avatar selection, chat, media generation, and retention. Drive conversion, retention, and LTV through hypotheses, prioritization, A/B testing, and data-informed design. Establish the product’s design direction and design system, lead a multidisciplinary design team, and partner with product, analytics, marketing, engineering, research, and support.

Oversee a portfolio of commercial accounts, ensure risk management, prepare credit analyses, monitor accounts, and liaise with clients including Fortune 500 executives.

Join Welo Data’s remote contributor network for future AI data projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy review. Contributors must have native or near-native Twi fluency, English proficiency, digital tool comfort, and strong attention to detail. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join a remote Albanian-language AI contributor network supporting flexible annotation, evaluation, and prompt-creation projects. Work may include labeling text, images, or audio; assessing search results, advertisements, and chatbot responses; creating prompts for large language models; and ensuring cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Freelance remote contributors support AI language-data projects through annotation, evaluation, prompt creation, and Korean-to-Chinese machine-transliterated lyric review. Responsibilities include assessing meaning, fluency, naturalness, and accuracy; rating quality against defined criteria; correcting errors; and providing feedback to improve AI systems. Projects are task-based, flexible, and dependent on availability.