Top AI Jobs in Dublin

Join Welo Data’s remote Sindhi AI trainer network for potential flexible projects involving text, image, or audio annotation; search-result, advertising, or chatbot evaluation; prompt creation and testing; and cultural and linguistic quality review. Contributors must be native or near-native Sindhi speakers based in India, proficient in English, comfortable with digital tools, detail-oriented, and curious. This is a talent-community opportunity rather than an active opening, with project details and compensation provided when assignments become available.

Join Welo Data’s Telugu AI contributor network for potential remote projects involving data annotation, search and chatbot evaluation, prompt creation, and cultural or linguistic quality review. Projects vary in length and compensation, with details provided before participation. Applicants must be based in India, fluent in Telugu and English, comfortable using digital tools, and detail-oriented.

Join a remote contributor network supporting AI training projects through text, image, and audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Kazakh fluency, English proficiency, digital tool comfort, and strong attention to detail are required.

Join Welo Data’s remote Afrikaans contributor network to support AI training projects through text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with compensation and timelines provided before each assignment. This is a talent-community application rather than an active job opening.

Join Welo Data’s Croatian talent network for potential remote AI projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural or linguistic accuracy reviews. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent community registration rather than an active job opening.

Join Welo Data’s Basque contributor network for potential remote AI projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent-network opportunity rather than an active job opening.

Join Welo Data’s remote Yoruba AI contributor network based in Nigeria. Projects may involve annotating text, images, or audio; evaluating search results, advertisements, or chatbot responses; creating prompts for large language models; and reviewing cultural and linguistic accuracy. Project duration, scope, timelines, and compensation vary. This is a talent community opportunity rather than an active job opening.

Join Welo Data’s Russian-language AI contributor network for flexible, remote projects involving text, image, and audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Contributors are contacted when suitable projects become available and receive project-specific details about tasks, timelines, and compensation.

Owns an AI investing product vertical end-to-end, including strategy, roadmap, technical design, delivery, metrics, and launch. Partners with engineering, compliance, finance, treasury, operations, and design to build reliable, auditable financial products. Responsibilities include API and data-flow design, ledgering, reconciliation, security, scalability, regulatory compliance, financial integrations, and responsible AI implementation with evaluation, safeguards, and human oversight.

Lead research and production development of LLMs and transformer models for machine translation and language quality. Design evaluation frameworks, agentic NLP workflows, training pipelines, and model-provider strategies. Own flagship model programs from data curation through production integration, mentor researchers, review technical work, and collaborate with Product and Engineering to ship capabilities. The role requires deep NLP and LLM expertise, rigorous experimentation, strong Python and ML library skills, and technical leadership.

Lead 0-to-1 product development for Kimchi’s AI coding and infrastructure products. Responsibilities include identifying high-value customer problems, conducting discovery, validating hypotheses, prioritizing opportunities, partnering with engineering and design, defining success metrics, driving adoption, and communicating product direction. The role requires strong judgment in ambiguous, rapidly changing technical markets and hands-on use of modern AI tools.

As a Principal Software Engineer, you will architect and lead AI Foundations projects, mentor engineers, and ensure quality standards across the AI platform.

Own the production improvement loop for Elastic’s Context Engine, improving AI agents, automations, retrieval, memory, telemetry, and evaluation. Design safe rollout processes, regression coverage, experiments, and quality, latency, and cost evaluators. Build production code in TypeScript or Python, collaborate with data science and product teams, mentor engineers, review designs, and influence the roadmap for agentic behavior and enterprise AI products.

Lead product direction, roadmaps, priorities, standards, and success metrics for major AI neobanking app areas. Guide PMs, product owners, designers, and engineers across multiple squads, balancing user experience, data, engineering, regulatory, operational, and business needs. Drive launch quality, post-launch learning, and continuous improvement across financial products including insurance, payments, savings, investing, and travel.

Lead product direction and outcomes for major areas of KIRA’s AI Investing App. Own strategy, priorities, roadmaps, product standards, metrics, launch quality, and continuous improvement across multiple squads and financial-service workstreams. Guide PMs, product owners, designers, and engineers while balancing UX, data, engineering, regulatory, operational, and business constraints. Mentor product teams, simplify complex financial products, and drive fast, measurable, user-focused execution in a high-growth environment.

Build and productionize generative AI and classical ML solutions for healthcare: data preparation, feature engineering, model/prompt development, evaluation, deployment, MLOps, monitoring, retrieval/indexing, and responsible AI practices while collaborating with cross-functional stakeholders.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Own AI Investing product areas across financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; use research, feedback, experiments, and performance data to improve decisions; and launch, monitor, and iterate features while balancing speed, user experience, business impact, compliance, and operational complexity.

Leads global commercial customer data governance, Customer 360 strategy, segmentation, data quality, reporting, and insight initiatives. Owns customer definitions and hierarchies across SAP and Salesforce, establishes governance and KPI standards, and aligns reporting and analytics investments with business value. Partners cross-functionally to improve data quality, reporting adoption, forecast accuracy, and AI readiness while driving change management and value realization across the commercial organization.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Build and evolve Salesforce Service Cloud, Omni-Channel, Agentforce, AI agents, customer channels, integrations, and intelligent automation. Develop Apex, SOQL, Flow, and Lightning Web Components solutions; connect Salesforce with external systems through APIs, events, and middleware; and establish testing, monitoring, security, and release practices. Partner with customer contact and technology teams to deliver scalable, measurable customer and agent experiences.

Own product marketing for Cyara’s Agentic AI assurance products, including positioning, messaging, go-to-market launches, competitive intelligence, sales enablement, technical content, and cross-functional collaboration. The role targets enterprise buyers through sales-led motions and requires measurable pipeline impact, strong writing and presentation skills, and comfort working with technical teams. Experience in AI, contact centers, QA, testing, observability, or monitoring is advantageous.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

Own end-to-end infrastructure delivery for strategic physical AI customers, from discovery and architecture through production rollout. Build cloud compute orchestration, platform services, onboarding environments, observability, security, and cost controls for simulation, training, inference, and batch workloads. Debug across infrastructure layers, productize recurring customer needs, and shape the physical AI platform roadmap. Partner with customers, Field CTO, Product, and Engineering while using AI coding tools to accelerate production engineering.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.