Design and build full-stack applications that integrate AI-driven physics simulation models into real-world engineering workflows. Collaborate directly with customers and technical teams to prototype, deploy, and iterate on high-impact tools across aerospace, energy, and advanced manufacturing. Work across backend services, APIs, and cloud infrastructure while contributing to core platform development.
Design and build full-stack applications that integrate AI-driven physics simulation models into real-world engineering workflows. Collaborate with data scientists and customers to develop, prototype, and deploy production-grade tools using Python, FastAPI, and cloud infrastructure. Work across industries such as aerospace, energy, and semiconductors, with opportunities for international travel to support on-site customer deployments and iterate on solutions based on direct user feedback.
Lead the development of the product management function within a high-impact AI consultancy, shaping standards and practices while delivering transformational AI solutions for enterprise clients. Work across technical, organisational, and strategic levels to bridge advanced AI models with real-world business outcomes. Operate in a hybrid role combining capability building, client advisory, and product execution.
Lead and develop the platform engineering team responsible for hybrid infrastructure, Kubernetes-based clusters, and scientific compute environments that support machine learning and drug discovery workflows. Define platform strategy, ensure robust CI/CD, observability, and security, and act as a technical leader across engineering and data science. The role involves shaping a developer platform tailored to computational scientists and genomic data pipelines in a high-impact TechBio environment.
Leads AI transformation programmes for professional services firms, shaping go-to-market strategy and building C-suite relationships. Guides multidisciplinary teams in delivering production-grade AI solutions that automate complex knowledge work and drive operational efficiency. Combines deep technical understanding with commercial acumen to grow Faculty’s practice in a regulated, high-impact sector.
Design and build full stack applications that enable users to interact with advanced computer vision and AI systems, focusing on image and video analysis, AI visualisation, and integration with customer infrastructure. Develop intuitive interfaces and workflows in collaboration with engineers and end users, with influence over architecture and technology choices. Work primarily on-site in West London, with some remote flexibility.
This role involves developing and optimizing cellular and biochemical assays using primary and immortalized cell lines, with a focus on fibrotic disease models. The scientist will conduct large-scale perturbation screens, apply multimodal readouts including transcriptomics and proteomics, and collaborate closely with cross-functional teams in biology, machine learning, and automation. Responsibilities include assay development, data analysis, and supporting the translation of workflows into high-throughput automated systems within a TechBio environment.
This Product Owner role involves shaping AI-native financial software by defining and prioritising backlogs, translating business needs into technical specifications, and collaborating with engineering teams. The role leverages AI tools daily to enhance requirements gathering, user story creation, and backlog management within autonomous agile teams. It focuses on delivering intelligent, enterprise-grade SaaS products for global banks and asset managers, with strong emphasis on AI-augmented workflows and data-driven product decisions.
This role involves building and optimizing ecommerce platforms, AI-driven customer communication agents, and automated workflows to enhance customer experience and business performance. The engineer will develop WordPress sites, integrate booking and payment systems, and implement AI solutions using OpenAI APIs, RAG, and vector search. Success is measured by increased conversions, reduced manual effort, and reliable AI automation integrated with CRM and customer service platforms.
Senior AI Governance ConsultantLondon, Manchester or Glasgow (Hybrid)£70k - £100k per annum + bonus and benefitsArtificial Intelligence is transforming the way organisations operate, but ensuring it's deployed safely, ethically and responsibly has never been more important.This is your opportunity to...
This role involves designing and building infrastructure tooling to support scalable, secure, and highly available deployment processes for a modern core banking platform. The engineer will develop automation, observability, and orchestration systems, working closely with data and streaming platforms in cloud environments. A key focus is enabling reliable operations for both internal engineers and bank SREs through robust tooling and CI/CD integration.
This role involves designing and prototyping generative machine learning models for protein design, with a strong focus on real-world biological applications. The scientist will build and evaluate models, collaborate across interdisciplinary teams, and iterate based on wet lab feedback. A significant emphasis is placed on high-performance code, scalable data pipelines, and staying current with advances in ML and synthetic biology.
Build and scale distributed web crawlers to source high-quality, multilingual data from the open web for training frontier AI models. Design targeted pipelines for audio, video, and text, and develop tooling for researchers to monitor and access crawled data efficiently. Focus on reliability, content extraction, deduplication, and compliance at web scale.
This role involves supporting the development and deployment of AI and machine learning models, working with large datasets, and collaborating with software engineers and product teams. You'll contribute to backend development, API integrations, and research new AI frameworks, ensuring responsible and ethical AI development.
This role involves driving the industrialisation of high-performance AI accelerator PCBAs from prototype to mass production, ensuring manufacturability, yield, and quality. The engineer will work hands-on with Taiwan-based manufacturing partners, lead DFM/DFT reviews, resolve real-time production issues, and build scalable processes for high-layer-count, fine-pitch boards used in advanced AI hardware. Success is measured by smooth NPI transitions, high first-pass yield, and robust design-for-manufacturing practices.
