Top AI Jobs in Belfast

Own AI Investing product areas across financial services, defining user problems, product scope, success metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Use research, feedback, metrics, experiments, and production insights to make decisions, launch features, monitor performance, and drive continuous improvement while balancing speed, user experience, business impact, compliance, and operational complexity.

Own product areas within an AI neobank across financial services such as insurance, payments, savings, investing, and travel. Define customer problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; use research, feedback, and performance data to iterate; and balance speed, user experience, business impact, compliance, and operational complexity.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans while collaborating with engineering, design, data, operations, compliance, and business teams. Simplify complex financial workflows, launch features, monitor performance, analyze feedback and metrics, and drive continuous improvements while balancing speed, usability, business impact, compliance, and operational complexity.

Administer and operate the NebulaOne AI platform and SIAP-delivered applications, including user access, configuration, licensing, monitoring, dashboards, maintenance, upgrades, incident resolution, and operational reporting. Maintain playbooks and recovery documentation, support automation workflows, deliver user training, and collaborate with developers, vendors, and university stakeholders to ensure reliable business-as-usual service delivery.

Lead an AI payments business end to end, owning P&L, strategy, product decisions, team building, execution, growth, partnerships, operations, revenue, and profitability. The role requires identifying customer and commercial opportunities, collaborating with product, engineering, and design teams, launching and improving products, and managing performance in a fast-paced, hands-on environment.

Lead an AI-native email app business end to end, owning P&L, strategy, product direction, team building, execution, growth, revenue, partnerships, operations, and profitability. Identify customer and commercial opportunities, decide what to build, collaborate with product, engineering, and design teams, launch and improve products, and drive measurable business outcomes in a hands-on operating role.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define product strategy, user problems, roadmaps, metrics, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial journeys; launch features; monitor performance; and drive continuous improvement through data, research, feedback, and experimentation.

Own product areas within AI Investing and other financial services, defining user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Use research, feedback, experiments, metrics, and production insights to launch quickly, measure performance, and continuously improve customer experiences while balancing business impact, compliance, and operational complexity.

Own the end-to-end product direction and quality of AI-powered email capabilities. Define requirements, evaluation frameworks, quality standards, and measurable outcomes while balancing model quality, latency, cost, reliability, safety, and user experience. Partner closely with ML, backend, and client engineers on system design, experimentation, failure handling, and iteration. Drive prioritization, technical decisions, execution, and user trust in a fast-moving zero-to-one environment.

Own AI stockbroking and other financial product areas from user problem definition through launch and iteration. Define product direction, scope, metrics, roadmaps, and launch plans while partnering with engineering, design, data, operations, compliance, and business teams. Simplify complex financial workflows, use research and performance data to guide decisions, manage trade-offs, and drive continuous improvement with high ownership.

Own AI Investing product areas and define user problems, scope, metrics, roadmaps, and launch plans. Partner with engineering, design, data, operations, compliance, and business teams to simplify financial products, ship features, monitor performance, and iterate using data, research, feedback, and production insights. Balance speed, user experience, business impact, compliance, and operational complexity while driving execution with high ownership.

Owns the end-to-end definition, evaluation, and quality of AI-powered email capabilities. Partners with ML, backend, client, and product teams to translate model behavior and technical constraints into requirements, system decisions, experiments, and roadmaps. Balances quality, latency, cost, safety, reliability, and user experience while identifying failure modes and building trustworthy, predictable AI features.

Lead the architecture and hands-on development of reliable AI-powered email applications across backend, mobile, and desktop platforms. Design orchestration, state management, tool use, retries, fallbacks, and failure handling for long-running workflows. Build production APIs, improve observability and reliability, make trade-offs involving latency, cost, security, and user experience, and lead a small senior engineering team through technical reviews, mentorship, and execution.

Lead the engineering strategy and execution for an AI-powered email application across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI capabilities to product experiences, lead a senior engineering team, make architecture and scalability decisions, and establish strong observability, monitoring, testing, security, and operational foundations. Partner with ML leadership to deliver fast, reliable, maintainable product experiences.

Leads application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Designs reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Builds APIs connecting AI capabilities to product experiences, makes architectural trade-offs, establishes observability and operational excellence, and leads a small senior engineering team through mentorship, design reviews, and code reviews. Partners with ML leadership to deliver scalable, reliable, and maintainable production systems.

Lead application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI systems to product experiences, make architecture and scalability decisions, mentor senior engineers, and establish strong observability, monitoring, testing, security, and operational practices. Partner with ML leadership to ship fast, reliable, maintainable product experiences.

Own product areas for an AI neobank across financial services such as insurance, payments, savings, investing, and travel. Define product direction, user problems, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial journeys; and use research, feedback, experiments, and performance data to continuously improve products.

Own product areas within AI Stockbroking and broader financial services. Define user problems, product direction, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams. Simplify complex financial products, use research and performance data to guide decisions, launch features quickly, and drive continuous post-launch iteration while balancing user experience, business impact, compliance, and operational complexity.

Own product areas within BJAK’s AI Neobank across financial services such as insurance, payments, savings, investing, and travel. Define user problems, product direction, roadmaps, metrics, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; and use research, feedback, experiments, and performance data to drive continuous improvements.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product strategy, roadmaps, metrics, launch plans, and customer journeys. Collaborate with engineering, design, data, operations, compliance, and business teams to ship features quickly, monitor performance, and iterate using data, research, feedback, and production insights. Balance user experience, business impact, compliance, operational complexity, and delivery speed.

Own product areas across AI investing and other financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Own AI engagement outcomes from success definition through production delivery. Design and evaluate end-to-end AI and GenAI systems, manage technical risk and trade-offs, communicate with clients, lead code reviews, resolve technical disagreements, mentor engineers, and develop reusable components and best practices. Deploy models and LLMs on AWS or Databricks with strong testing and CI/CD practices.

Industry Expert who sets the technical bar for advanced AI, ML, systems, or forward-deployed engineering programs. Responsibilities include reviewing deployed projects, leading technical defenses and mock review boards, delivering occasional live sessions, critiquing architecture and tradeoffs, and advising instructors on difficult design decisions. The role requires production-scale engineering experience, senior-level judgment, a public technical footprint, strong English, and comfort with AI tools. It is fully remote and requires approximately 4–10 hours monthly.

Leads the identification, development, integration, and global deployment of AI and automation solutions for legal editorial, metadata, and content operations. The role supports AI strategy, evaluates designs against governance and quality standards, manages cross-functional projects, reports data-driven outcomes, tracks industry trends, documents improvements, and promotes responsible AI use.