Top AI Jobs in Belfast

Design, build, and operationalize agentic AI systems for clinical imaging trials: intake/validation (DICOM/non‑DICOM), RAG-grounded workflows, QC checks, evaluation harnesses, MLOps deployment, observability, safety/traceability, and cross-functional enablement across the PDLC.

Design and build core backend systems for an agent platform: orchestration, durable execution, memory, tool integration, observability, and evaluation. Create scalable services/APIs, develop retrieval and long-term memory solutions, monitor and improve agent behavior, and help drive technical direction and team growth for AI-driven collaboration features.

Senior individual contributor researching how threat actors weaponize AI across the attack lifecycle. Instrument telemetry, analyze global data and OSINT, develop detections, automate research workflows with LLMs and scripting, and publish external threat intelligence to inform protections and operations.

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.

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.

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 manage a cross-functional engineering team to design, build, and operate a high-scale payments app. Drive architecture, delivery, code quality, reliability, observability, and incident response while coaching engineers and improving processes to ship customer-focused products quickly and reliably.

Lead and grow a high-performing engineering team building scalable, customer-facing products. Own engineering delivery, architecture, code quality, observability, incident response, and engineering culture. Partner with product, design, mobile, backend and AI teams to turn ambiguous problems into production systems while coaching engineers and improving processes to deliver reliable, high-quality outcomes.

Lead technical design and execution of products for an AI-enabled payments app. Hands-on coding, architecture, system design, code review, debugging, production ownership, mentoring engineers, improving dev tooling, and collaborating with product, design and AI teams to ship reliable, scalable systems.

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 develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable payment and AI-integrated products. Own technical architecture, delivery, code quality, observability, incident response, and engineering processes while coaching engineers and driving product-focused outcomes.

Technical lead responsible for designing, building and operating scalable full-stack systems. Hands-on coding, architecture decisions, code reviews, mentoring, cross-team collaboration, production reliability, observability and driving features from concept to production.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable production systems. Own technical architecture, delivery, code quality, observability, incident response, and engineering processes while coaching engineers and driving product outcomes in partnership with product, design, mobile, backend and AI teams.

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.

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.

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

Mentor apprentices on an AI Champion programme by assessing progress, supporting portfolio development and EPA preparation, providing technical advice and regular feedback, contributing to curriculum content, safeguarding learners, and liaising with employers and the Delivery Team to drive AI adoption.

Mentor apprenticeship learners to identify and implement AI-driven workflow improvements, assess progress against the apprenticeship standard, support portfolio and EPA preparation, provide technical support and mentoring sessions, report learner progress, and uphold safeguarding and equality responsibilities.

Work as a quantitative consultant delivering insight programmes that combine advanced analytics, mixed methods and AI to solve client problems. Contribute to analysis, synthesize evidence, build consultancy skills, explore AI tools, support business growth and help shape proposals and client-facing work.

Drive research and engineering for large-scale LLM and multi-modal pre-training: design architectures, curate massive datasets, run distributed training on multi-node GPU clusters, optimize performance, and advance cross-modal alignment and efficiency.