Top AI Jobs in Dublin

Design, build, and scale AWS cloud infrastructure and AI-enabled systems. The role owns CI/CD pipelines, containerized and serverless applications, data pipelines, security, disaster recovery, high availability, automation, testing, and operational documentation. It collaborates with engineering, business, and operations teams to deliver reliable solutions aligned with organizational goals, while participating in Agile practices and evaluating emerging cloud and DevOps technologies.

Design, train, evaluate, optimize, and deploy advanced machine learning models for drug discovery. Own the full model lifecycle, build scalable inference and MLOps pipelines, establish reproducibility and testing standards, validate models with scientific experts, and mentor teams. The role focuses on deep learning, graph-based architectures, foundation models, distributed training, model monitoring, and production performance across latency, throughput, cost, and reliability requirements.

Own Productboard’s AI product strategy and roadmap, including the Spark agent, orchestration harness, AI UX, evaluation quality, feedback insights, product specifications, MCP integrations, dashboards, and design system. Lead product managers and designers, establish quality standards and critique processes, determine UI versus headless agent experiences, and drive adoption of agentic workflows across Productboard.

Leads consultative Cloud and AI solution sales for mid-market customers, guiding cloud transformation across infrastructure, data, and AI platforms. Responsibilities include customer engagement, pipeline and forecast management, solution demonstrations, business-case development, proofs of concept, partner coordination, and closing revenue opportunities. The role requires technical fluency, Turkish proficiency, and experience exceeding sales targets while collaborating with account executives, solution architects, engineers, and partners.

Drive enterprise sales of Microsoft AI Workforce and cloud solutions across French- and Dutch-speaking markets. Identify customer needs, generate pipeline, develop business value propositions, build executive relationships, lead generative AI narratives, and close solution sales opportunities. Collaborate with technical specialists, partners, and consultants to execute account plans, forecast opportunities, cross-sell and up-sell Modern Work solutions, and exceed sales targets.

Embed with strategic customers to design, build, and implement data-driven AI solutions that improve customer support automation and Fin adoption. Analyze workflows and business challenges, establish measurement best practices, prototype and scale AI tools, and collaborate with Sales, Success, Product, and Engineering. Feed deployment insights back into product strategy while translating complex technical analysis into measurable business outcomes.

Develop a pro-human strategy for AI emphasizing controllable, verifiable, human-centered systems. Track efficient models, open-source AI, robotics, and industrial applications; engage international policymakers and stakeholders; build coalitions; and translate technical strategy into policy recommendations. The role requires strong AI technical fluency, policy engagement experience outside the US and China, excellent communication, stakeholder management, and independent strategic leadership.

Build and ship customer-specific AI automations and agents embedded in creative workflows and tools. Own the studio automation roadmap, convert recurring requests into reusable systems, define quality checks, collaborate with Product, train customers, and document solutions for reuse across studios.

Lead the architecture and delivery of scalable, secure cloud-native platforms across public clouds. Define reference architectures, engineering standards, governance controls, observability practices, and reusable developer-platform capabilities. Drive responsible adoption of generative and agentic AI in engineering workflows, including validation, auditability, security, and data protection guardrails. Partner with architecture, engineering, product, security, risk, and business teams while mentoring technical talent and setting enterprise architecture direction.

Design, build, and operate LLM-powered applications and agentic AI workflows for employee platforms. Productionize models and services, implement monitoring and SLOs, create CI/CD and testing, build data/retrieval layers, ensure governance and security, and partner with product, SRE, security and data teams to integrate AI capabilities.

Own end-to-end improvements to Oyster AI, including agent capabilities, tool calling, retrieval, evaluation, infrastructure, and production reliability. Ship LLM-powered features, diagnose failures, manage quality, latency, cost, safety, and access-control trade-offs, and validate improvements through experiments and regression checks. Mentor product teams, establish reusable AI engineering patterns, and collaborate asynchronously across engineering and product.

Secure enterprise AI, generative AI, and agentic AI systems from design through production. Implement AI guardrails, prompt-injection and jailbreak protections, secure tool calling, least-privilege access, API and application security, runtime monitoring, threat modeling, security testing, logging, SIEM integration, and compliance controls. Partner with cybersecurity, IAM, cloud, data, engineering, legal, privacy, product, and vendor teams to develop practical, repeatable security patterns for responsible AI delivery.

Designs scalable QA automation and AI evaluation frameworks across web, APIs, data pipelines, and LLM-powered systems. Builds Playwright and TypeScript test infrastructure, integrates quality gates into CI/CD, reduces flakiness, and supports shift-left engineering practices. Develops evaluation pipelines using golden datasets, semantic scoring, and LLM-as-a-judge methods. Tests agentic workflows, security risks, performance, and distributed systems while improving observability, defect triage, and release confidence.

Designs scalable QA automation and AI evaluation frameworks across web, APIs, data pipelines, and LLM-powered features. Establishes risk-based testing, quality gates, CI/CD integration, observability, defect triage, and non-functional security testing. Partners with engineering, data science, product, and SRE teams to enable shift-left quality ownership. Evaluates AI systems for hallucinations, prompt injection, drift, retrieval failures, and agentic workflow risks using golden datasets, semantic scoring, and LLM-as-a-judge approaches.

Freelance AI Specialist responsible for completing and maintaining a shared business knowledge base, improving AI workflows with Claude and Gemini, creating reusable prompts, connecting AI to business tools, documenting processes, training teams, and reporting progress. The role requires careful fact-checking, strong written communication, confidentiality judgment, basic scripting or automation skills, and self-directed project execution.

MBA Summer Associates join consulting teams for 8–12 weeks, contributing to real client projects and developing hands-on strategy consulting experience. Responsibilities include strategic analysis, creative problem-solving, teamwork, and applying AI-based solutions and data competencies to complex business challenges. Strong performers may receive full-time offers.

Own the full sales lifecycle for Harvey’s AI solutions, from prospecting and product demonstrations through contracting, onboarding, expansion, and renewals. Manage named mid-market accounts, build executive relationships, exceed revenue targets, forecast pipeline, and conduct consultative value-based sales. Collaborate with product and engineering teams, tailor solutions for legal and professional services clients, contribute to sales playbooks, and travel occasionally to customer and company offices.

Drive mid-market sales of Harvey’s AI solutions to law firms and corporate and financial services clients. Responsibilities include prospecting, managing the full sales cycle, conducting tailored demonstrations, achieving revenue targets, maintaining pipeline forecasts and CRM hygiene, cultivating stakeholder relationships, collaborating cross-functionally, and contributing to sales playbooks and processes.

Own the SMB sales cycle for Harvey’s AI solutions, from prospecting and qualification through demonstrations, negotiations, and contracting. Manage pipelines, forecasts, CRM hygiene, revenue targets, and executive relationships. Tailor consultative solutions for small law firms and in-house legal teams, collaborate with product and engineering, and develop sales tactics, messaging, collateral, and resources to improve team performance.

Drive new business growth among small law firms and in-house legal teams. Manage the full sales cycle from prospecting and qualification through demonstrations, solution validation, negotiation, and contracting. Own pipeline management, forecasting, CRM hygiene, revenue targets, and executive stakeholder relationships. Collaborate with product and engineering teams to tailor AI solutions, while developing sales tactics, messaging, collateral, and process improvements for the SMB sales organization.

Leads and coaches a team of SMB Account Executives selling an AI platform to law firms and corporate legal teams across EMEA. Owns territory planning, pipeline generation, forecasting, revenue execution, sales-process discipline, deal reviews, and team performance. Acts as a player-coach on strategic deals while developing sales systems, mentoring representatives, and reinforcing consultative, value-based selling practices.

Leads cloud and AI go-to-market activation across sales, marketing, consulting, customer success, and partner teams. Owns product positioning, scorecard metrics, GTM planning, partner enablement, pipeline growth, market differentiation, seller readiness, and supply-demand alignment. Serves as a product spokesperson and cross-functional orchestrator while guiding team performance, strategic execution, and business development in a multinational matrixed organization.

Lead production AI initiatives including LLM agents, AI drafts, and a shared Context Engine. Own architecture decisions, evaluation systems, guardrails, observability, reliability, and quality measurement. Deliver major AI projects from design through production while providing cross-functional technical leadership and improving engineering standards. Build backend and platform infrastructure using Python, Django, PostgreSQL, Redis, asynchronous workers, and REST or GraphQL APIs.

Lead Oddin.gg’s technology organization and an AI-focused business unit. Partner with the CEO on strategy, priorities, commercial outcomes, and execution. Guide engineering, infrastructure, technical leadership, and data science teams while developing leaders and accountability. Drive practical AI, LLM, and automation capabilities into production, and ensure real-time platforms remain reliable, secure, scalable, and cost-effective.

Leads enterprise customer engagements for Microsoft Cloud and AI solutions, guiding cloud transformation across infrastructure, data, and AI platforms. Owns the sales lifecycle, pipeline, forecasting, customer commitment, consumption, and expansion. Partners with account executives, solution engineers, architects, services teams, and partners to develop business cases, run workshops, scope proofs of concept, close opportunities, and drive Azure adoption. Requires technical fluency, consultative selling skills, enterprise sales experience, and German and English fluency.