Top AI Jobs in Belfast

Develop end-to-end AI product features by integrating LLMs and external tools, ensuring system reliability and performance across multiple tasks.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

The role focuses on deploying AI SDR agents and optimizing sales processes through automation, enhancing productivity across the revenue team while requiring hands-on experience in AI implementation in B2B sales environments.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and translate analytics into product recommendations to shape AI product strategy.

The Senior .Net Developer will enhance SDG's C#/.NET Core codebase, design high-load services, and optimize MS SQL queries, benefiting from a remote work environment and attractive benefits.

Leads global AI regulatory, accreditation, and certification activities for BSI’s certification and notified bodies. Develops conformity assessment activities, policies, procedures, documentation, and certification schemes aligned with ISO standards, the EU AI Act, Medical Devices Regulation, and other global requirements. Ensures assessor expertise and rigor, provides technical input on AI lifecycle and management-system assessments, and represents BSI in industry forums and stakeholder groups.

Lead and operationalize a company-wide AI governance program: build frameworks, assess AI risks and use cases, embed controls in SDLC, run governance council, liaise with Siemens consortium, handle regulatory compliance (EU AI Act, NIST AI RMF), produce reporting, and deliver training and documentation across Product, Engineering, Legal, Privacy, HR and Security.

Lead research and engineering for large-scale LLM and multi-modal pre-training: design architectures and tokenizers, curate massive datasets, run distributed training on thousands of GPUs, debug performance bottlenecks, and improve cross-modal alignment and efficiency.

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

Work as a consultant combining human insight, strategy and AI to deliver client insight programmes. Synthesize diverse evidence, apply methodology and emerging technologies, support proposals and business growth, and develop consultancy and analytics skills across sectors.

Lead and deliver AI-enabled insight programs, manage client accounts, combine human, cultural and artificial intelligence methods, grow client relationships and revenue, coach and develop teams, shape propositions and ways of working to evolve insight consultancy.

Design, prototype, and deploy generative AI systems (RAG, agents) and integrate LLMs with data sources and production systems. Build cloud-native solutions, apply LLMOps and model evaluation, and collaborate cross-functionally to deliver scalable AI products.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Lead global R&D to define technical strategy and roadmaps, prioritize AI-driven modernization, manage engineering and test teams, oversee AI/ML model validation in regulated clinical environments, own R&D budgeting and vendor partnerships, ensure regulatory compliance, and drive operational excellence and ethical AI adoption to improve clinical trial outcomes.

Full-stack AI/ML Software Engineer to build HealthTech SaaS microservices, implement and integrate ML solutions, write high-quality code, author documentation, perform code reviews, and act as an SME on services and systems.

The AI Engineer designs, develops, and deploys AI-driven applications for non-data scientists, enhancing decision-making and model accessibility for organizations.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

Lead Mark43's AI-enabled engineering initiative by designing and orchestrating multi-agent systems that plan, write, review, test, and deploy software. Write prompts, scaffolding, and tool integrations (VCS, test runners, internal APIs), evaluate agent performance, prototype LLM-based workflows, collaborate cross-functionally, mentor teammates, and contribute to on-call rotations.

Conduct deep technical research to identify novel risks and attack vectors in cloud- and AI-native architectures, produce proofs-of-risk and technical POCs, and partner with Product and Engineering to translate findings into product capabilities.

Drive new-logo acquisition for AI and cloud infrastructure customers across UK&I. Own end-to-end enterprise sales cycles, execute outbound prospecting, design multichannel outreach, close large-scale data center and cloud deals, and collaborate cross-functionally to deliver GTM strategies and partner relationships.

Deliver and operationalize AI learning and adoption programs across the firm: run workshops, cohorts, office hours, champion activities, learner support, stakeholder engagement, learning operations, and measurement to embed responsible AI into workflows and drive adoption.

Design, build, and ship LLM-backed agentic systems that call tools, query client data, orchestrate specialist agents, and run against cloud or on-prem models. Scope proofs of concept into maintainable solutions, collaborate with client engineers, build reusable accelerators, and explain design decisions to technical and non-technical stakeholders.