Top AI Jobs in Belfast

As a Staff Backend Engineer at GitLab, you'll enhance backend infrastructure for CI, integrate AI features, and ensure reliability and performance in CI/CD workflows.

Lead technology and AI strategy for the AI Business Solutions practice, focusing on Dynamics 365, Power Platform and Microsoft AI. Define architecture, governance, repeatable Copilot/agent patterns, and technical standards; engage C-suite customers and Microsoft; drive capability investment, IP/accelerators, and senior technical capability development to scale commercially viable AI solutions.

The Senior Application Development Lead will drive Generative AI adoption across multiple applications, ensuring best practices, system quality, and technical leadership while collaborating with global teams.

Support productionising AI/ML solutions for Workday products under senior guidance. Collaborate with data scientists and engineers to deploy, monitor, and maintain models using cloud, containerisation, and MLOps practices while following responsible AI and data privacy guidelines.

Manage the Onboarding Risk team across regions, ensuring high-quality risk decisions, developing team members, and owning onboarding risk procedures. Support complex escalations, collaborate cross-functionally, and keep processes compliant with card scheme rules and payments legislation while improving KPIs and decision frameworks.

Lead design, development, and deployment of scalable Data & AI solutions on Databricks and Microsoft Foundry. Define AI technical roadmap, mentor an AI engineering squad, partner with stakeholders to prototype and scale AI products, and ensure governance, security, and ethical AI practices across enterprise platforms.

Design and build scalable Azure platform capabilities for AI (Agents, RAG, LLMs), create reusable platform components (APIs, gateways, model-serving), produce high-quality technical designs, optimize performance/cost, and collaborate across teams to enable AI at scale.

Build and ship native Android features in Kotlin (Jetpack Compose). Integrate backend APIs, improve performance and reliability, collaborate with product and design, use analytics, and implement AI-assisted on-device experiences where valuable.

Build and ship native Android features using Kotlin and Jetpack Compose. Design clean user flows for financial services, integrate backend APIs, improve performance and stability, use analytics and production feedback, and implement AI-assisted on-device experiences where beneficial.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.

Design, implement, and optimize AI-driven solutions across the claims lifecycle (intake, investigation, adjudication). Build ML models for data extraction, fraud detection, reserve setting, subrogation, and adjudication decision engines. Collaborate with underwriting, fraud, legal, and IT to integrate models into operations and improve efficiency, accuracy, and compliance.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Lead modernization of month-end and year-end close processes using AI and automation. Prepare, review, and validate journal entries, accruals, and financial statements. Implement anomaly detection, automated reconciliations, variance analysis, and predictive insights. Collaborate with data teams to structure finance data for ML use cases and design audit-ready, scalable reporting workflows.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Analyze and classify technical content for security vulnerabilities, apply pattern recognition to improve AI model threat detection, design and evaluate security problems, and collaborate asynchronously with domain experts to produce high-quality outputs.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Lead AI-enabled financial planning and strategic analysis, build data-backed business cases, refine unit economics, deliver executive-level insights, integrate ML into FP&A, and track KPIs to drive profitability and strategic decisions.

Manage and optimize end-to-end account reconciliations, intercompany eliminations, and chart-of-accounts governance. Identify discrepancies, perform variance analysis, and implement AI-driven automation and anomaly detection to reduce manual effort and accelerate close. Collaborate with cross-functional teams to resolve mismatches and improve financial data quality and reporting accuracy.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

The AI Implementation Engineer delivers and stabilizes AI solutions in customer environments, ensuring integrations and workflows meet requirements while coaching customer teams during critical phases.

Design and ship production agents and reusable skills on ClickStack. Own the agent stack (context engineering, tools, MCP servers), integrate with ClickHouse telemetry, build SDKs and observability, optimize latency/cost, run evals, and collaborate with open-source contributors and customers.