Top AI Jobs in Manchester

Owns an AI finance product vertical end-to-end, including strategy, roadmap, technical design, delivery, launch, metrics, and regulatory readiness. Partners with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Applies AI with evaluation, safeguards, human oversight, and reliability controls while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance. Requires experience with complex technical products, regulated financial domains, and AI or LLM-powered products.

Own a financial 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. Incorporate regulatory requirements, financial rails, and third-party dependencies. Apply AI and LLMs with evaluation, safeguards, human oversight, and reliability controls while aligning cross-functional teams.

Own a financial 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. Embed regulatory requirements across KYC, monitoring, limits, privacy, and licensing. Apply AI and LLMs with evaluation, safeguards, oversight, and reliability controls while aligning compliance, operations, treasury, finance, design, and engineering.

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

Owns an AI neobank product vertical end-to-end, including strategy, roadmap, technical design, delivery, regulatory requirements, AI evaluation, reliability, and launch. Partners with engineering, compliance, operations, treasury, finance, and design across payments, remittance, insurance, wealth, and trading products. Must balance correctness, scalability, security, user experience, cost, speed, and regulatory constraints in high-consequence financial systems.

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.

Entry-level technical consultants develop skills across cloud, data engineering, DevOps, security, software engineering and AI-enabled technology. They build and troubleshoot solutions, automate infrastructure, implement CI/CD, improve platform security, work with cloud services, and support client delivery. The programme includes structured training, mentoring, certifications and hands-on project experience. Successful candidates communicate clearly, solve problems logically, learn new technologies and contribute to reliable, secure and maintainable enterprise solutions.

Own data workstreams across transformation programmes, including planning, data quality assessment, cleansing, validation, analysis, dashboards, reporting, stakeholder engagement, governance, and issue resolution. Translate data into actionable insights and support coordination across projects. Contribute to internal tools, delivery methods, and continuous improvement while developing consulting and data delivery capability.

Lead end-to-end data workstreams within higher education transformation programmes. Responsibilities include planning, governance, data quality, reporting, integration approaches, stakeholder engagement, risk and dependency management, workshops, team coaching, adoption of improved data practices, and support for bids and thought leadership. Requires advanced SQL, structured dataset expertise, dashboard development, strong analytical problem-solving, and consulting communication skills.

Develop and evaluate AI/ML and Generative AI/LLM models from POC to production, perform data science and statistical analyses to support business decisions, document and assess model risk, publish patents/papers, collaborate with SMEs, and provide technical leadership while deploying solutions with modern Agile/DevOps and cloud practices.

The Senior Power Electronics Application Engineer will develop high-reliability power solutions for AI and data centre systems, including designing hot-swap protection and providing technical support to global teams.

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.

Owns AI learning programs from intake through completion, including Bootcamps, webinars, hackathons, and enablement sessions. Coordinates speakers, mentors, participants, logistics, communications, and live event execution. Develops hands-on tasks, capstones, rubrics, and assessments with instructional design partners. Tracks attendance, completion, certification outcomes, satisfaction, and proficiency data while maintaining learning-content repositories and governance standards.

Develop scalable full-stack web applications, backend services, APIs, and AI-powered features for Roku’s advertising platform. Build RAG chatbot solutions, optimize distributed systems, write tests, support CI/CD, improve delivery processes, and deploy customer-facing features. Collaborate with UX, engineering, DevOps, QA, and product teams while solving complex reliability and performance challenges. The role requires modern web development, cloud platforms, AI-assisted engineering workflows, and strong software architecture practices.