As a Senior AI Engineer at PoliceAI, you will lead the design, development, and deployment of AI-enabled products, translating policing needs into technical solutions. You will work with multidisciplinary teams to build secure, maintainable, and scalable services, and support the testing, evaluation, and validation of AI products.
As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.
This role involves building technical relationships with global and regional system integrators and cloud partners, enabling their AI practices, and supporting strategic customer deals. You will also gather product feedback and represent Anthropic at partner events.
This role involves leading end-to-end technical deployments of cutting-edge AI models for strategic customers, from prototyping to production. The engineer will build full-stack systems, deeply integrate with customer teams, and translate field feedback into product and model improvements. Success is measured by real-world adoption and measurable impact on customer workflows.
This role involves leading end-to-end deployments of cutting-edge AI models into production environments for strategic customers. The engineer will work full-stack, building systems that integrate generative models while deeply collaborating with customer teams to understand needs and drive adoption. Success is measured through real-world impact and feedback that shapes product and model development.
The AI Forward Deployed Engineer role involves developing cutting-edge GenAI solutions, rolling out production-grade applications, and serving as a technical advisor to customers. You will collaborate with product and engineering teams to shape strategic priorities and present at industry conferences.
This role involves leading and scaling a team of AI/ML professionals, developing executive relationships with EMEA customers, and driving strategic initiatives. The role requires deep technical expertise in ML, GenAI, and data science, as well as experience in managing and growing high-performing teams.
This role involves conducting forensic data analysis to detect and investigate financial crime, fraud, bribery, corruption, and regulatory breaches within financial services. You'll work with large structured and unstructured datasets using advanced analytics techniques, including machine learning and social network analysis, to support high-profile investigations. The position emphasizes end-to-end project delivery, client communication, and mentoring junior analysts in a sensitive, high-stakes environment.
This role involves designing and building scalable data platforms using Databricks, SQL, and modern cloud technologies. You will work closely with stakeholders to transform complex data challenges into innovative solutions, driving data-driven decision-making and AI adoption across the organisation.
This role involves designing, building, and maintaining large-scale, fault-tolerant hybrid cloud networks that support CrowdStrike’s global cybersecurity platform. The engineer will work across multiple cloud providers and on-prem data centers, focusing on IP and optical technologies, automation, and network reliability at massive scale—processing trillions of events daily. The position requires deep expertise in routing protocols, infrastructure-as-code, and AI-driven operational improvements, with a strong emphasis on scalability, security, and innovation.
You will work on optimizing large language models for performance and scalability within a cutting-edge AI-driven drug discovery environment. The role involves implementing post-training methods, diagnosing bottlenecks in distributed systems, and deploying low-precision techniques to support real-world drug design applications. Collaboration with interdisciplinary research teams is central to translating novel AI methods into production-ready systems.
Develop and optimise cutting-edge AI models at the intersection of machine learning and drug discovery, translating research into scalable, production-ready systems. Work closely with scientists to build predictive and generative models using advanced deep learning techniques, with a focus on innovation in computational biology and chemistry. Contribute to a collaborative, interdisciplinary team advancing a digital biology platform for transformative medicine development.
This summer internship programme at Barclays' Client Data & Engineering Group (CDEG) involves working on real projects that combine data, analytics, and AI to generate insights for financial markets. Interns will collaborate with cross-functional teams, build dashboards and visualizations, and contribute to data-driven tools and workflows.
Lead a London-based engineering team building critical connectivity infrastructure for AI agents, including the MCP proxy, OAuth systems, and token management. Drive reliability, security, and scalability across distributed systems used in enterprise environments. Collaborate closely with San Francisco teams to shape the future of agent tool integration and contribute to open standards.
Design and implement production-grade AI and ML systems, focusing on Agentic AI, RAG, and LangChain/LangGraph patterns. Establish engineering standards, improve observability and model risk controls, and drive adoption across engineering teams. Work within a regulated environment to enable safe, scalable AI solutions in production.
Design and build scalable cloud-based detection systems that process billions of events daily to identify sophisticated threats across multi-cloud environments. Work closely with security researchers to translate threat intelligence into automated, real-time detection capabilities using distributed systems and data engineering techniques. Develop and optimize components like custom query languages, event orchestration, and correlation engines within a modular, AI-native security platform.
This role involves teaching, research, and academic leadership in the field of digital health and AI. Responsibilities include co-leading the Introduction to Digital Health module, contributing to curriculum development, supervising Master’s dissertations, and developing an independent research programme with a focus on responsible and equitable innovation.
