Top AI Jobs in Manchester

Lead technical direction for an AI platform connecting workloads to multiple LLM providers. Build API gateway and routing infrastructure, agent orchestration, capability lifecycle tooling, access controls, API key management, caching, cost and latency optimization, adoption analytics, and trust, safety, and governance controls. Define API standards and promotion workflows while supporting auditable, scalable AI services across client engagements.

Drive AI adoption across an M&S business unit by identifying and embedding use cases into workflows, tracking value and adoption, coaching colleagues, building champion networks, communicating success stories, and feeding business needs into the AI Accelerator. Ensure adoption aligns with responsible AI, fair usage, and data governance frameworks.

Serve as the embedded AI adoption partner for a business unit, identifying and embedding AI use cases into workflows, including Copilot Studio agents and automation. Drive measurable adoption and value, coach colleagues through role-specific training, communications, and champion networks, and share business insights with the wider AI Accelerator. Ensure AI usage aligns with responsible AI, fair usage, and data governance frameworks.

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.

Design, develop, and deploy intelligent AI agents, optimize large language models, enable collaboration in customer interactions, and maintain backend systems.

Perform remote transcription, annotation, and voice data collection tasks in native English. Accurately transcribe audio/video, label and classify data per guidelines, record voice samples, and meet quality, productivity, and formatting standards.

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.

Lead AI regulatory compliance within a global bank: strengthen AI governance, assess regulatory risk, advise stakeholders, draft guidance and regulator responses, maintain compliance dashboards, and drive alignment across Legal, Risk, and Engineering.

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.

Delivers workshops, webinars, office hours, mentoring, technical support, and assessments for Digital Product Manager apprentices. The role provides learner feedback, supports portfolio development and apprenticeship endpoint assessment preparation, monitors progress, contributes to quality assurance and content development, and helps learners prepare for Gateway. Candidates need product management experience, user-centred design, Agile methods, business analysis, process modelling, change management, teaching or mentoring experience, and a relevant Level 4 qualification or certification.

Drive Azure Cloud and AI partner sales across Microsoft Education and Nonprofit customers. Develop partner sales plans, build pipeline, execute co-sell strategies, progress priority deals, manage renewals and upsell motions, coordinate internal and external stakeholders, and deliver consultative, outcome-focused Azure solution selling. The role requires Azure technical fluency, disciplined pipeline management, partner activation, and achievement of sales metrics.

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

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, compliance, operations, and business teams; simplify complex financial workflows; launch features; monitor performance; and drive continuous iteration using data, research, feedback, and production insights.

Own AI Investing product areas across 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 workflows, launch features, monitor performance, use research and feedback to iterate, and balance speed, user experience, business impact, compliance, and operational complexity.

Own product areas for AI stockbroking 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 journeys; use metrics, research, feedback, and production issues to improve decisions; launch features, monitor performance, and drive iteration.

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 products, launch features, monitor performance, use research and feedback to guide iterations, and balance speed, user experience, business impact, compliance, and operational complexity.

Own product areas for an AI-focused neobank across financial services such as insurance, payments, savings, investing, and travel. Define user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to ship and improve products. Use research, feedback, experiments, and performance data to make prioritization and trade-off decisions while simplifying complex financial workflows.

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 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.