Top AI Jobs in Bristol

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 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 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.

Lead and grow a team of AI Solution Architects to design, govern, and operationalize enterprise-scale AI and conversational solutions. Define AI architecture strategy, standards, and governance; advise customers and executives; support sales and product direction; collaborate cross-functionally to build reusable AI frameworks; and drive responsible AI, observability, reliability, and adoption to deliver measurable business outcomes.

Senior Director analyst providing thought leadership and actionable research on infrastructure and operations AI strategy. Produce insights, presentations, and client advisories; guide AI infrastructure, cloud adoption, integration, governance, and vendor selection. Lead research agenda, mentor analysts, collaborate cross-functionally (infrastructure, engineering, enterprise architecture, cybersecurity), support sales, and represent Gartner at events. Drive process improvements and influence senior stakeholders to align infrastructure and operations with business outcomes.

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.

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.

Lead the customer-facing conversational agent across chat and voice: own roadmap, design conversations and interfaces in Figma, build prototypes, define agent behavior and quality metrics, partner with enterprise clients and implementation teams, and iterate from production conversation data to improve resolution, containment, and escalation.

Review, evaluate, and annotate AI-generated content (text, audio, images, video). Identify errors and quality issues, select best outputs, provide written feedback, follow detailed guidelines, attend trainings, and complete tasks remotely within deadlines.

Lead and manage a cross-functional engineering team to design, build, and operate a high-scale payments app. Drive architecture, delivery, code quality, reliability, observability, and incident response while coaching engineers and improving processes to ship customer-focused products quickly and reliably.

Lead and grow a high-performing engineering team building scalable, customer-facing products. Own engineering delivery, architecture, code quality, observability, incident response, and engineering culture. Partner with product, design, mobile, backend and AI teams to turn ambiguous problems into production systems while coaching engineers and improving processes to deliver reliable, high-quality outcomes.

Lead technical design and execution of products for an AI-enabled payments app. Hands-on coding, architecture, system design, code review, debugging, production ownership, mentoring engineers, improving dev tooling, and collaborating with product, design and AI teams to ship reliable, scalable systems.

Lead technical design and delivery of AI-native email applications. Own architecture and implementation across backend, frontend, APIs, databases and cloud. Stay hands-on writing and reviewing code, debugging production, mentoring engineers, driving major initiatives, improving tooling, and ensuring reliability, security and observability while collaborating with product, design and AI teams.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable payment and AI-integrated products. Own technical architecture, delivery, code quality, observability, incident response, and engineering processes while coaching engineers and driving product-focused outcomes.

Technical lead responsible for designing, building and operating scalable full-stack systems. Hands-on coding, architecture decisions, code reviews, mentoring, cross-team collaboration, production reliability, observability and driving features from concept to production.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable production systems. Own technical architecture, delivery, code quality, observability, incident response, and engineering processes while coaching engineers and driving product outcomes in partnership with product, design, mobile, backend and AI teams.