Top Tech Jobs & Startup Jobs in Dublin

Lead a team building and deploying foundation models and generative AI solutions. Drive end-to-end delivery from problem definition to production, partner with stakeholders, ensure data readiness and MLOps, establish evaluation and responsible AI practices, and coach engineers to deliver reliable, scalable AI use cases.

Design, build, and maintain full-stack web applications and scalable data pipelines for analytics products. Implement responsive UIs, backend data models, and performant APIs. Ensure high-quality, well-tested code, mentor junior engineers, improve development processes, and collaborate with product, design, and cross-regional teams to deliver customer-centric analytics solutions.

Lead a cross-functional engineering team to design, build, and deliver full-stack web applications and data pipelines. Provide technical direction, mentor engineers, drive product roadmaps, implement scalable solutions, and collaborate across teams to solve complex problems while contributing as a hands-on developer.

Design, develop, and deploy enterprise-grade AI solutions using LLMs, RAG, and vector-search knowledge bases. Build scalable, secure cloud-native systems (AWS, Cloudera, Databricks), APIs, and microservices; implement LangChain and MCP patterns; monitor and optimize production model performance; ensure data governance and compliance; mentor engineers and drive engineering best practices.

Lead architecture and design for a global B2B payments platform, create technical blueprints and service contracts, mentor engineering teams, ensure security, resiliency, scalability, conduct design/code reviews, and align implementations with cloud-native and Mastercard standards.

Lead security advocate for Data Commercialization and AI programs. Advise product and engineering teams on secure design, translate security policies into actionable guidance, lead security reviews and governance (threat modeling, code/design reviews, 3rd-party assessments), embed security in SDLC and CI/CD, and drive protection of sensitive data and ML models through automation and standards compliance.

Lead a team developing and deploying foundation models and generative AI solutions. Drive end-to-end delivery from problem definition to production, collaborate with product, data engineering, and platform teams, establish evaluation and responsible AI practices, and provide technical leadership and coaching to ensure robust, scalable, measurable AI use cases.

Lead engineering team building and operating API platforms and backend services to expose foundation model capabilities. Own architecture, security, scalability, observability, CI/CD, and reliability. Partner with AI teams to integrate models, manage multiple workstreams, hire and develop talent, and translate product needs into technical roadmaps.

Lead engineering strategy and hands-on delivery for agentic AI products and platforms. Build and scale teams and reusable agent frameworks, drive architecture for production-grade LLM/agent systems (context, memory, tool integration, orchestration, observability, safety), partner with Product and Data Science, and establish engineering standards, tooling, and measurable success criteria to move experiments into governed, scalable production.

Lead and deliver production-grade agentic AI systems and platforms. Define engineering vision, build and scale teams, architect agent frameworks and orchestration, ensure security, observability, and governance, partner with Product and Data Science, and drive adoption of AI tooling and developer productivity across the organization.