AI Engineer/Developer
Our client is in the Financial Sector and is looking to grow their team with a new AI Engineer. The role is hybrid with 2 days in Central London, 3 days at home. This is a brand new role in...
Our client is in the Financial Sector and is looking to grow their team with a new AI Engineer. The role is hybrid with 2 days in Central London, 3 days at home. This is a brand new role in...
Design and build generative AI applications using Python, React, and AWS, with a focus on LLMs, RAG pipelines, and AI agents. Integrate AI capabilities into existing systems and collaborate with technical and business teams to deliver production-grade solutions in a financial services environment.
This is a fantastic opportunity to join Luminance, the pioneer of Legal-Grade™ AI for enterprise. Backed by internationally renowned VCs and named in both the Forbes AI 50 list of ‘Most Promising Private AI Companies in the World’ and Inc....
Lead the end-to-end delivery of AI solutions, from strategy and proof of concept to production deployment, with a focus on LLMs, RAG pipelines, and AI agents. Collaborate across data, infrastructure, and business teams to integrate scalable AI tools into enterprise workflows and drive measurable operational impact.
Design and operate a scalable AI platform supporting RAG pipelines, LLM orchestration, and vector search on Microsoft Azure and Microsoft Foundry. Focus on productionising prototypes into resilient, observable, and secure services using infrastructure-as-code, CI/CD, and cloud-native practices. Collaborate with AI Engineering, DevOps, and Info-Sec to ensure reliability, performance, and compliance at scale.
Design and deploy AI solutions using Microsoft Azure, integrating with business systems like Microsoft 365, SharePoint, and SQL databases. Develop production-grade LLM and machine learning applications, focusing on RAG, forecasting, and anomaly detection. Work closely with stakeholders to translate business needs into secure, scalable AI implementations within a construction and manufacturing context.
An Applied AI Engineer will work directly with enterprise customers to design, build, and deploy AI systems that solve real-world business problems. The role involves hands-on coding, system integration, and technical leadership to guide AI solutions from prototype to production, with a focus on reliability, safety, and measurable impact. The position requires deep technical expertise and strong collaboration with both customer teams and internal OpenAI groups.
An Applied AI Engineer will work directly with enterprise customers to design, build, and deploy production-grade AI systems that solve high-impact business problems. The role involves hands-on coding, architecture design, integration, evaluation, and guiding technical decisions across safety, reliability, cost, and governance. Engineers will transition prototypes into scalable, reliable systems while contributing reusable tooling and influencing product development through real-world deployment insights.
Design and implement production-grade Agentic AI, Generative AI, and RAG systems that power customer-facing SaaS products. Develop autonomous agents with reasoning, planning, and workflow execution capabilities, integrated with multi-agent orchestration and advanced retrieval. Collaborate with platform and engineering teams to deploy scalable AI solutions on Microsoft Azure.
This role involves designing and building scalable AI data pipelines and cloud-native microservices, with a focus on productionising machine learning, NLP, and generative AI models. The engineer will collaborate closely with data scientists and software engineers to transform research into robust, cloud-based systems using modern MLOps practices. Emphasis is placed on technical leadership, mentoring, and shaping engineering standards within a global AI team.
This role involves leading the end-to-end development of enterprise AI products, from concept to market launch, with a focus on translating business challenges into AI-driven solutions. The engineer will work closely with data scientists and stakeholders to build production-grade AI systems using LLMs, RAG architecture, and agentic workflows, particularly within financial services. The position requires strong technical expertise in Python and AI platforms, alongside product strategy and stakeholder engagement.
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 designing, building, and integrating AI applications into end-to-end workflows, embedding agentic AI into customer and operational processes, and collaborating with cross-functional teams to deliver robust, production-ready solutions. The focus is on turning emerging AI capabilities into practical, high-value implementations while ensuring reliability, resilience, and safety.
Build and ship end-to-end AI agent systems that transform how Multiverse operates, from context design and tool integration to evaluation and production operation. Work across the full stack to reinvent internal workflows and set the blueprint for AI-first companies. Use AI-assisted development with Claude Code and shape technical direction in a small, high-impact team.
Leads technical AI projects involving high-throughput vision systems on NVIDIA Jetson hardware, with a focus on real-time tracking, multi-modal sensor integration, and AI assurance. Provides technical leadership across the design lifecycle and mentors junior engineers. Works in multidisciplinary teams and engages with stakeholders to shape project direction and innovation in edge AI systems.