Top AI Jobs in Belfast

Lead development of a generative AI proof-of-concept and integrate AI solutions into software workflows. Mentor data engineers, design and implement Python-based generative AI applications, build scalable data pipelines, deploy models/APIs, and translate stakeholder requirements into technical solutions while staying current on AI and data engineering best practices.

Design, build, and maintain production-ready full-stack applications combining React frontends with Java/Python backends. Integrate Generative and Agentic AI workflows, implement CI/CD, deploy cloud-native services on Kubernetes (GCP/Azure), manage relational and NoSQL databases, apply automated testing, observability, and troubleshoot production systems while collaborating across DevOps, QA, and Product teams.

Lead and grow a team of AI Solution Architects to design, govern, and operationalize enterprise-scale AI and conversational solutions. Define AI architecture strategy, standards, and governance; advise customers and executives; support sales and product direction; collaborate cross-functionally to build reusable AI frameworks; and drive responsible AI, observability, reliability, and adoption to deliver measurable business outcomes.

Lead go-to-market strategy and commercial execution for a new AI-native Market Research service. Build positioning, pricing, and metrics; generate pipeline and close deals; partner with Sales, Marketing, Product, and Research; represent Maze publicly; and help scale the service and team while feeding market insights back into product and offering design.

Lead execution of enterprise AI strategy, prioritise and scale high-value AI, automation and data initiatives, govern responsible AI practices, drive end-to-end delivery and adoption, and align stakeholders to realise measurable business outcomes.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Define and build Fuse's inference-serving architecture and stack, including request routing, batching, scheduling, and autoscaling for latency-sensitive workloads. Own model-level optimizations (quantisation, distillation, speculative decoding), translate performance SLAs into capacity plans, and integrate low-level GPU/CUDA performance work with serving infrastructure. Set benchmarks, tooling, and act as technical owner of inference performance and reliability.

Deploy and maintain AI enablement infrastructure (MCP servers, AI agents, hosting) and cloud environments on AWS/GCP. Build IaC and CI/CD pipelines, monitor performance/cost, support containerized services, manage API keys and permissions, document runbooks, and collaborate with Security, Engineering, and stakeholders to improve cloud governance and AI tooling adoption.

Build and evolve a real-time AI tutoring system: design prompt architectures and agentic workflows, run experiments and custom evaluations, integrate models with platform infrastructure, prototype production model interactions, ensure safety and observability, and collaborate with educators and product teams to translate pedagogy into technical solutions.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

Lead end-to-end product design for complex, data-intensive workflows across web, desktop, and mobile. Run user research and validation, craft flows, wireframes, prototypes, and polished interfaces. Partner with product and engineering, use data and design judgment to improve outcomes, and contribute to design systems, patterns, and cross-team collaboration. Advocate for AI-enabled UX where applicable.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

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.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will innovate in model compression techniques for large multimodal AI systems, focusing on efficiency and model deployment.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will optimize model serving and inference architectures, focusing on high-performance, resource-efficient solutions for AI systems across various deployment environments.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

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.

Architect and build agentic workflows combining LLMs, reasoning, and data pipelines. Lead ML/NLP product development from training to deployment, drive experimentation, integrate intelligent agents into recruiting workflows, mentor engineers, and improve reliability, personalization, and observability.

As a Product Manager, you will lead AI-first pods, drive product roadmaps, prioritize customer needs, and collaborate effectively across teams to deliver AI-powered solutions.

The Technical Artist will aid in optimizing an AI-driven creative production pipeline, transforming concepts into high-quality 3D outputs, troubleshooting technical issues, and maintaining asset organization.

The Senior AI Transformation Consultant works with clients to identify AI opportunities, define robust business cases, and oversee AI project deployments, ensuring solutions deliver value.

This role involves mentoring apprentices in AI technologies, providing assessments, support in project development, and fostering learner relationships.