Top AI Jobs in Manchester

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.

Lead the enterprise AI function, strategy, roadmap, platforms, engineering capability, governance, adoption, and delivery. Build a central AI team, help product and business teams deploy AI solutions, establish safe and compliant guardrails, manage AI-related costs, run pilots through production, and measure business impact. The role also drives training, change management, and AI champion networks across the organization.

Develop and scale NVIDIA Inception’s European startup ecosystem by identifying, technically assessing, recruiting, enabling, and nurturing AI and accelerated-computing startups. The role advises founders and technical leaders on CUDA, NVIDIA SDKs, AI frameworks, GPU infrastructure, and platform adoption; leads technical workshops; translates ecosystem feedback into product insights; collaborates with venture capital firms and internal teams; and supports sales and enterprise customer motions. Travel across Europe is required approximately 40% of the time.

Leads the identification, development, testing, and scaling of AI and automation solutions across internal delivery processes and future customer-facing use cases. Builds automated test suites, scripts repetitive workflows, pilots generative AI and agentic tools, creates reusable automation assets, tracks measurable value, and enables teams through training and knowledge sharing. Collaborates with project managers, product owners, process owners, testing communities, and delivery teams to ensure maintainable, responsible, and broadly adopted solutions.

Lead and scale an EMEA team of AI and experience orchestration overlay sellers. Coach specialists, establish operating models, drive AI-focused sales motions, partner with Account Executives and sales leadership, support strategic enterprise opportunities, and translate customer challenges into AI use cases and measurable value. Monitor market and competitive trends while collaborating with Product, Marketing, Enablement, Customer Success, and Professional Services to improve go-to-market effectiveness.

Create daily 60–90-second vertical AI micro-drama episodes for TikTok, Instagram Reels, and YouTube Shorts. Responsibilities include generating scenes with AI tools, editing footage in 9:16 format, maintaining character consistency, syncing music and sound effects, adding timed captions and overlays, and optimizing exports for social platforms. The role requires rapid experimentation, prompt engineering, knowledge of editing and composition, and experience with AI-generated video, static content, and audio.

Create daily 60–90-second vertical micro-drama episodes for TikTok, Instagram Reels, and YouTube Shorts using AI video, image, and audio tools. Generate scenes, edit footage in 9:16 format, maintain character consistency, synchronize music and sound effects, add captions and overlays, and optimize exports for social platforms. The role requires prompt engineering, visual composition, and editing skills, with traditional production and storytelling experience considered advantageous.

Lead technology and AI strategy for the AI Business Solutions practice, focusing on Dynamics 365, Power Platform and Microsoft AI. Define architecture, governance, repeatable Copilot/agent patterns, and technical standards; engage C-suite customers and Microsoft; drive capability investment, IP/accelerators, and senior technical capability development to scale commercially viable AI solutions.

Lead AI architecture for an agentic LLM assistant (Protege) in PatentSight+. Define AI architecture, evaluate models and platforms, design retrieval/vector search and RAG pipelines, author ADRs, establish prompt engineering and evaluation frameworks, ensure security/privacy/compliance, and partner with product, data, and platform teams to deliver production-grade AI systems.

Owns NVIDIA’s EMEA go-to-market motion for its Agentic AI Platform. Drives customer and partner adoption across enterprise, AI-native, cloud, public sector, defense, and regulated environments. Develops sales enablement, reference architectures, field guidance, and adoption strategies covering open models, security, governance, deployment, licensing, and confidential computing. Coordinates with technical, product, legal, security, engineering, and ecosystem teams while translating complex AI platform capabilities into commercially effective sales plays and revenue outcomes.

Lead AI architecture and consulting engagements for UKI customers, supporting sales, scoping, workshops, solution architecture, statements of work, and business development. Develop reusable AI consulting solutions, enable regional teams, and lead the design and implementation of complex AI systems. Advise customers on AI value, predictive and generative models, MLOps, model serving, guardrails, agentic systems, and observability. Regular travel across London and Dublin is required.

Support sales by designing and demonstrating Cisco cloud, data center, and AI-ready infrastructure solutions. Engage customers to assess modernization goals, craft platform architectures, present technical value, run workshops, and collaborate with account teams and partners to drive adoption of compute, storage, networking, and cloud-native technologies.

Design, build, and deploy production-scale AI systems including multi-agent workflows, RAG pipelines, and fine-tuned LLMs. Deliver full-stack web and backend integrations, develop evaluation frameworks and monitoring, iterate prototypes into production, and shape internal best practices for applied AI.

Lead end-to-end delivery of AI projects for the European maritime portfolio, managing scope, schedule, budget, risk, quality, and client relationships. Coordinate teams of 5–10 technical and domain specialists across multiple concurrent engagements, enforce delivery standards, forecast resources and financials, report portfolio performance, and drive continuous improvement.

Coordinate and support end-to-end delivery of AI projects, liaising with clients and technical teams, maintaining plans/logs/reports, troubleshooting delivery issues, ensuring quality and validation, and contributing to knowledge sharing and cross-service AI initiatives.

Lead client-facing discovery and pre-sales for AI solutions, design end-to-end AI architectures and roadmaps, shape proposals and SOWs, ensure smooth handoffs to delivery, and collaborate with the AI Center of Excellence to build reusable assets and governance-aware solutions.

Designs enemies and NPC behaviors for a high-mobility multiplayer action game. Creates design specifications and technical documentation, collaborates with designers and engineers on scripting and behavior trees, analyzes player data and feedback to improve AI, coordinates dependencies with producers, and pitches new AI concepts to leadership.

Lead client-facing technology consulting and solution development for large, complex cloud, data, and AI transformations. Advise C-suite stakeholders, identify growth opportunities, shape Microsoft and AWS-powered roadmaps, develop value propositions, and guide commercial, technical, and delivery models. Direct solution teams, proposals, statements of work, peer reviews, and approvals while contributing to industry points of view and transformation methodologies. Strong expertise in Microsoft Fabric, Foundry, cloud architecture, managed services, outsourcing, and agile and waterfall delivery is required.

Designs, develops, tests, and supports Java-based cloud-native applications on Google Cloud Platform. Builds REST APIs, integrates AI services, applies secure coding practices, contributes to CI/CD and deployment automation, and implements observability through logging, metrics, dashboards, and alerts. Troubleshoots production issues, performs root-cause analysis, participates in architecture discussions and code reviews, collaborates across engineering and business teams, and mentors junior developers.

Partner with investment teams to identify high-value AI use cases, design lightweight proofs-of-concept, enable users through training and best practices, provide light technical support, and track adoption and impact of AI solutions across EMEA research teams.

Manage the Onboarding Risk team across regions, ensuring high-quality risk decisions, developing team members, and owning onboarding risk procedures. Support complex escalations, collaborate cross-functionally, and keep processes compliant with card scheme rules and payments legislation while improving KPIs and decision frameworks.

Translate TecAlliance business problems into production-ready AI solutions: define use cases, prototype with ML/LLM components, iterate with stakeholders, and hand over to production while documenting and scaling best practices.

Leads research and thought leadership on AI-driven HR strategy, transformation, governance, workflow redesign, regulatory environments, and value realization. Produces actionable insights across written, visual, video, and presentation formats; advises CHROs and senior HR leaders; analyzes market trends, vendors, technologies, and client challenges; supports sales and conferences; mentors analysts; and improves research processes.

Lead the AI function, define roadmap, and build production generative AI systems (voice, chat, document). Split time between hands-on engineering (~40%) and leading the AI team, establishing RAG/agentic workflows, evaluation, observability, and best practices. Collaborate with product and engineering to deliver reliable, user-focused AI features.

Lead architecture and build a production AI Media Production platform delivering 1:1 product-accurate image and video assets. Ship modular, versioned generative pipelines (node-based or code-first), train LoRAs end-to-end, integrate control-first methods (ControlNet, IP-Adapter, inpainting, reference conditioning), deploy internal GPU-backed tools and one-click UIs, and embed automated QC against product references. Partner with design to own roadmap, qualify models/tools, and enable creative teams.