Top AI Jobs in Dublin

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.

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.

As an AI/ML Engineer, you will develop and optimize AI solutions for renewable energy assets, collaborating with a skilled team to deploy algorithms in real-world projects.

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.

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.

As a Senior Data Scientist at Intercom, you'll analyze data to drive decisions, support product teams, build data pipelines, and influence product strategy using AI tools.

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.

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

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.

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.

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.

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.

Build and ship AI-driven GTM systems: outbound lead engine, inbound/lifecycle automations, AI-assisted content pipeline, data/reporting layer, and fast production patches to eliminate manual marketing workflows.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

Teach and mentor experienced engineers transitioning to system architecture: run live sessions and office hours, review student architecture deliverables, lead architecture review boards, provide written feedback, record instructional videos, and support a team of instructors. Focus areas include system design, APIs, cloud/platform, distributed systems, security, and AI systems design.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

The role involves evaluating AI outputs, generating content, and providing feedback for model improvement while ensuring cultural relevance and accuracy. Candidates should possess native language fluency and strong analytical skills.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design and ship a 14-domain skills taxonomy and SDK/CLI tooling, operate the MCP server, integrate agent protocols, improve LLM grounding for crypto, run developer hackathons, and produce technical content to grow the ecosystem.