Top AI Jobs in Manchester

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.

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.

Build and deploy AI-powered applications, agents, copilots, and intelligent workflows for enterprise clients. Translate ambiguous business problems into scalable architectures and production software using LLMs, Generative AI, APIs, enterprise systems, and data sources. Rapidly prototype solutions, validate them with users, and implement monitoring, evaluation, and feedback mechanisms. Collaborate with technical and business stakeholders to move successful AI solutions into production while clearly communicating recommendations.

Leads the strategic development, governance, and evolution of TM Forum’s Open Digital Architecture, with a focus on AI and data. Collaborates with telecom and technology stakeholders to create architecture artifacts, align standards, guide implementations, manage roadmaps, and drive adoption. Represents TM Forum through industry thought leadership and explains complex technical concepts to diverse audiences. Requires extensive enterprise or solution architecture experience, cloud-native expertise, API design knowledge, and strong stakeholder communication skills.

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.

Lead presales, GTM and demand-generation for Cyber & AI Security. Own proposals and pipeline, coordinate architects and engineers, manage partner (Microsoft) engagement, convert delivery into case studies, and feed market signals into Product and Services.

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.

Lead CMS and web platform modernisation efforts, prototype AI/agentic POCs, and support the Principal Engineer to shape technical direction. Investigate where AI adds value, refocus the CMS team on higher-value marketing work, improve scalability and management, and collaborate with stakeholders to define pragmatic technical approaches and roadmap.

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.