Top AI Jobs in Manchester

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

Work as a consultant combining human insight, strategy and AI to deliver client insight programmes. Synthesize diverse evidence, apply methodology and emerging technologies, support proposals and business growth, and develop consultancy and analytics skills across sectors.

Lead and deliver AI-enabled insight programs, manage client accounts, combine human, cultural and artificial intelligence methods, grow client relationships and revenue, coach and develop teams, shape propositions and ways of working to evolve insight consultancy.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

Full-stack AI/ML Software Engineer to build HealthTech SaaS microservices, implement and integrate ML solutions, write high-quality code, author documentation, perform code reviews, and act as an SME on services and systems.

The AI Engineer designs, develops, and deploys AI-driven applications for non-data scientists, enhancing decision-making and model accessibility for organizations.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

Lead Mark43's AI-enabled engineering initiative by designing and orchestrating multi-agent systems that plan, write, review, test, and deploy software. Write prompts, scaffolding, and tool integrations (VCS, test runners, internal APIs), evaluate agent performance, prototype LLM-based workflows, collaborate cross-functionally, mentor teammates, and contribute to on-call rotations.

Own end-to-end enterprise sales in the Nordics/UK for a security platform that maps internet-exposed assets and runs automated AI penetration testing and DAST. Build territory plan and pipeline, engage technical buyers (CISOs, AppSec, Security Engineers), run demos and POCs with Sales Engineering, close complex six-figure ACV deals, and establish regional playbooks and partnerships.

Deliver and operationalize AI learning and adoption programs across the firm: run workshops, cohorts, office hours, champion activities, learner support, stakeholder engagement, learning operations, and measurement to embed responsible AI into workflows and drive adoption.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Own and improve Primer's GTM intelligence: maintain dashboards and semantic models, train BI/LLM models (Omni/Claude), surface pipeline/account signals, ensure correct Salesforce modeling, build revenue-driving models and GTM AI workflows, partner with data engineering and RevOps, drive adoption, and promote self-serve data literacy.

Lead design, implementation, and production operation of agentic LLM systems for medical imaging clinical trials. Build end-to-end agentic workflows (planning, retrieval, tool use), RAG solutions, evaluation frameworks, scalable backend services, and MLOps pipelines. Provide technical leadership, mentor engineers, ensure observability, compliance, and safety, and translate clinical workflows into validated, production-grade AI systems.

Design, build, and operationalize agentic AI systems for clinical imaging trials: intake/validation (DICOM/non‑DICOM), RAG-grounded workflows, QC checks, evaluation harnesses, MLOps deployment, observability, safety/traceability, and cross-functional enablement across the PDLC.

Design and build core backend systems for an agent platform: orchestration, durable execution, memory, tool integration, observability, and evaluation. Create scalable services/APIs, develop retrieval and long-term memory solutions, monitor and improve agent behavior, and help drive technical direction and team growth for AI-driven collaboration features.

Design polished, user-centric mobile and web interfaces for BJAK's AI and financial products. Create wireframes, flows, prototypes and high-fidelity UI, evolve the design system, collaborate with PMs and engineers, iterate using user feedback and analytics, and ensure accessibility, responsiveness and visual consistency.

Senior individual contributor researching how threat actors weaponize AI across the attack lifecycle. Instrument telemetry, analyze global data and OSINT, develop detections, automate research workflows with LLMs and scripting, and publish external threat intelligence to inform protections and operations.

The role involves developing AI/ML applications using Python, implementing REST APIs, collaborating with data scientists, and maintaining software quality through testing and CI/CD processes.

As a Senior Staff Software Engineer, you'll lead technical architecture on the Maia team, drive AI feature development, mentor engineers, and collaborate on product vision within a fast-paced, evolving environment.

Lead go-to-market strategy and commercial execution for a new AI-native Market Research service. Build positioning, pricing, and metrics; generate pipeline and close deals; partner with Sales, Marketing, Product, and Research; represent Maze publicly; and help scale the service and team while feeding market insights back into product and offering design.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Deploy and maintain AI enablement infrastructure (MCP servers, AI agents, hosting) and cloud environments on AWS/GCP. Build IaC and CI/CD pipelines, monitor performance/cost, support containerized services, manage API keys and permissions, document runbooks, and collaborate with Security, Engineering, and stakeholders to improve cloud governance and AI tooling adoption.

Build and evolve a real-time AI tutoring system: design prompt architectures and agentic workflows, run experiments and custom evaluations, integrate models with platform infrastructure, prototype production model interactions, ensure safety and observability, and collaborate with educators and product teams to translate pedagogy into technical solutions.