Top AI Jobs in Dublin

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

Create short- and long-form AI-generated educational and entertainment content for Instagram, TikTok, and YouTube. Rapidly test content hypotheses, analyze performance, research trends and competitors, and iterate on hooks, storytelling, and editing. Collaborate with the product team and continually experiment with AI image/video generation and editing tools.

Lead and build Maze’s new AI-native Market Research service: define research vision and methodologies, recruit and manage a research team, own delivery quality, partner with Product/Engineering and GTM, and serve as executive research lead on strategic customer engagements.

Create high-quality video content and integrate AI tools into production workflows, combining storytelling and video craft to enhance cinematic quality.

The Director of Business Development will drive revenue through creating strategies for new business, managing client relationships, and overseeing sales processes while ensuring high service standards.

Design, build, and maintain ELT pipelines and dbt SQL models for analytics; optimize performance, scalability, and costs; apply AI-enabled tools to improve engineering workflows; collaborate to translate requirements into production-grade data assets.

As an AI Creative Producer, you'll develop and scale AI-generated content across various platforms, collaborate with teams, and enhance production workflows.

Manage early-stage grantmaking for the Transformative AI Fund: evaluate applications, recommend grants, source opportunities, support grantees, build partnerships, represent the fund, and develop systems and LLM-assisted tooling to improve grant processes.

Design, develop, test, and ship AI-powered features and agent/LLM workflows for large datasets. Rapidly prototype, iterate with users, integrate agentic components with internal tools, and ensure scalable, production-grade AI solutions using cloud-native and observability practices.

Design, build, and deploy production-grade agentic AI systems: multi-agent orchestration, RAG pipelines, provider abstraction, LLMOps (eval harnesses, prompt versioning, observability), cloud-native deployment (Kubernetes/Docker/CI-CD/IaC), and embed with client teams to deliver reusable patterns and measurable metrics for accuracy, latency, safety, and cost.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

Build and productize AI-native systems for a fintech neobank: AI agents, RAG/LLM-powered workflows, tool integrations, and automations for onboarding, KYC, support, risk, CRM and operations. Focus on production reliability, evaluation, guardrails, latency, cost, security and compliance while collaborating with product and engineering teams.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

Lead engineering and operations for enterprise AI (M365 Copilot) solutions: design, deploy and optimise Copilot, build integrations and connectors, ensure security and governance, run operational lifecycle, mentor engineers, and drive adoption with stakeholders.

Lead large, complex customer deployments of Intercom and Fin, define scope and success metrics, manage timelines and stakeholders, perform hands-on platform configuration and integrations, coordinate technical readiness and data migrations, track adoption and outcomes, and evolve deployment methodology and best practices.

Lead strategy and execution for AI-powered asynchronous engagement across messaging, email, and proactive/predictive journeys. Define vision, measurable outcomes, and portfolio priorities; partner with AI, engineering, and go-to-market teams; engage customers; build and coach a product organization to operationalize AI at enterprise scale and deliver measurable automation and CX improvements.

Remote, part-time role testing an AI tool in Irish: perform guided tasks, report results, follow onboarding and troubleshooting, use MS Teams and basic apps, ~1–3 hours/day up to 15 hrs/week for at least two months, paid $20–$35/hr.

Architect and build an AI-native automation and orchestration toolchain (fusing traditional tools with foundation models), enable and mentor early adopter teams, standardize practices across departments, drive infrastructure-as-code and CI/CD adoption, contribute to the IT/Sec operating system, and champion cross-departmental adoption of automation and AI platforms.

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

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.