Top AI Jobs in Belfast

Own an AI-native stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reliability, security, and scalability. Incorporate regulatory requirements across KYC, monitoring, limits, privacy, and licensing. Apply AI with appropriate evaluation, safeguards, oversight, and failure handling while aligning engineering, compliance, operations, finance, and external partners.

Build and lead an AI-native stockbroking business, defining its proposition, roadmap, business model, and AI-powered investing experiences. Own P&L, funded accounts, assets, trading activity, revenue, unit economics, brokerage infrastructure, custody, market data partnerships, licensing, regulatory readiness, and expansion. Collaborate with product, engineering, and AI teams, while recruiting and scaling the core team.

Build and lead BJAK’s AI-native finance business, defining product strategy, roadmap, business model, and market expansion. Identify financial workflows improved by AI, develop products from concept through scale, and own P&L, growth, revenue, unit economics, and operations. Collaborate with product, engineering, and AI teams while building cross-functional teams across technology, operations, and commercial functions.

Own an AI stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reliability, security, scalability, and failure handling. Integrate regulatory requirements across KYC, transaction monitoring, limits, privacy, and licensing. Apply AI responsibly with evaluation, safeguards, human oversight, and clear failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Build and lead an AI-native stockbroking business, defining its proposition, product roadmap, business model, and AI-powered investing experiences. Own P&L, growth, trading activity, revenue, unit economics, brokerage infrastructure, partnerships, licensing, regulatory readiness, and market expansion. Collaborate with product, engineering, and AI teams while building the core team and scaling technology products and operations.

Build and lead an AI-native digital banking business, defining its proposition, roadmap, business model, and customer experiences. Own P&L, deposits, revenue, unit economics, operating costs, and growth. Partner with product, engineering, and AI teams to develop accounts, cards, payments, savings, and money-management products. Build the leadership team, establish banking and operational capabilities, manage partnerships and regulatory readiness, and expand into new markets.

Build and own an AI-native consumer investing business, defining its proposition, roadmap, business model, and investment experiences. The CEO will own P&L, assets, customers, engagement, revenue, and unit economics; lead product, engineering, AI, investment, technology, and commercial teams; and expand into new products and markets. The role requires deep investing or fintech experience, product judgment, consumer technology scaling experience, and hands-on operating capability.

Own an AI investing product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Embed KYC, transaction monitoring, privacy, licensing, and other regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and reliability controls while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Owns an AI neobank product vertical end to end, including strategy, metrics, roadmap, technical design, delivery, and launch. The role involves shaping reliable financial systems across APIs, data flows, ledgering, reconciliation, security, scalability, and regulatory requirements. Responsibilities include applying AI with safeguards and evaluation, managing financial rails and third-party dependencies, and aligning engineering, design, compliance, operations, treasury, and finance. Candidates need strong technical product management experience in regulated financial or other high-consequence domains.

Lead a team of controls professionals to translate AI behavior into actionable controls, prototype scalable AI/automation controls, run red-team exercises, steward AI control standards, and engage senior stakeholders to prioritize and deploy AI-enabled control solutions across Asset & Wealth Management.

Lead AI controls enablement by translating AI risks into practical controls, partnering with Controls, Business, and Technology to design scalable solutions, perform risk reviews, implement controls, and advise senior stakeholders to ensure compliant AI adoption.

As an AI Inference Engineer, you will optimize C++ systems for AI model inference on edge devices, collaborating with researchers to deploy and enhance models while ensuring runtime stability and performance.

Owns end-to-end architecture and hands-on implementation for an AI-driven investment platform. Designs production-grade LLM and RAG systems, data and integration architectures, security standards, and Azure cloud infrastructure. Builds prototypes and production code in Python and TypeScript, reviews designs, establishes reusable patterns, leads technology evaluations, and mentors engineering teams. The role partners with investment, risk, finance, and senior technology stakeholders to deliver scalable, secure, compliant, and cost-effective solutions.

Develop, deploy, and maintain scalable AI/ML pipelines and production models, including LLMs and generative AI. Optimize model performance, latency, and cost across AWS, GCP, and Azure. Apply MLOps practices such as CI/CD, versioning, monitoring, logging, and maintenance. Collaborate with data scientists, software engineers, solution architects, and cross-functional teams to integrate AI capabilities into products and workflows.

Build and deploy AI-powered products for investment, portfolio, risk, finance, and legal teams. Own full-stack production solutions spanning data ingestion, APIs, AI orchestration, frontend interfaces, cloud infrastructure, security, governance, observability, and operations. Develop RAG, agentic workflows, document intelligence, and AI-generated analytics while working directly with senior stakeholders. Rapidly prototype solutions, iterate using user feedback, champion engineering quality and responsible AI practices, and mentor other engineers.

Own product areas within AI stockbroking and financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial journeys. Launch features, monitor performance, use research and feedback to guide iterations, and balance speed, user experience, business impact, compliance, and operational complexity.

Architect, design and deliver production-grade AI solutions using ML, generative and agentic AI. Lead technical delivery, implement RAG/prompt engineering, ensure responsible AI, drive cloud-native, scalable architectures, mentor and manage junior engineers, and collaborate with clients to translate business needs.

Owns an AI-focused finance product vertical from strategy through launch, including outcomes, metrics, prioritization, technical design, money movement correctness, reliability, compliance, and AI evaluation. Partners with engineering, design, compliance, operations, treasury, and finance to manage regulatory gates, trade-offs, failure handling, and trusted user experiences. Requires strong technical product leadership, system design knowledge, regulated-domain experience, and hands-on familiarity with LLM-based products.

Lead product direction and execution for major areas of KIRA’s AI Investing App. Own roadmaps, priorities, product standards, success metrics, launch quality, and post-launch improvement across multiple squads and financial-service products. Guide PMs, product owners, designers, and engineers while balancing user experience, data, engineering, regulatory, operational, and business needs. The role requires strong judgment, comfort with ambiguity, and the ability to simplify complex financial products.

Leads product direction and execution for major areas of an AI-powered finance and neobank app. Owns roadmaps, priorities, product standards, success metrics, launch quality, and continuous improvement across multiple squads and financial services, including insurance, payments, savings, investing, and travel. Guides product managers, designers, and engineers while balancing user experience, data, engineering, regulatory, operational, and business considerations.

Own product areas for KIRA’s AI Stockbroking App and other financial services. Define user problems, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; use research, feedback, metrics, and production issues to guide decisions; launch features, monitor performance, and drive continuous iteration while balancing speed, user experience, business impact, compliance, and operational complexity.

Lead technical pre-sales for AI and data opportunities across the UK public sector. Shape solution strategies, conduct client workshops, lead bids and procurements, advise on responsible AI adoption, and develop differentiated AI propositions. Provide expertise in generative and agentic AI, machine learning, LLM solutions, data foundations, governance, evaluation, and production adoption. Build senior stakeholder relationships, support demonstrations and proofs of concept, mentor colleagues, and ensure proposed solutions are practical, secure, scalable, ethical, and deliverable.

Own product areas for KIRA’s AI Investing App and related financial services. Define user problems, scope, metrics, roadmaps, and launches; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; and use research, feedback, metrics, and production issues to iterate quickly while balancing user experience, business impact, compliance, and operational complexity.

Own product areas across financial services within KIRA’s AI neobank app. Define customer problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial workflows, launch features, monitor performance, and iterate using data, research, feedback, and production insights.

Own AI Investing product areas by defining user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, ship features quickly, monitor performance, and iterate using data, research, feedback, and production insights. Balance speed, customer experience, business impact, compliance, and operational complexity.