7 of 7 Remote Retrieval-Augmented Generation Jobs in the South East

AI expert ready to take your skills to the next level? Do words like Azure OpenAI, Cognitive Services, prompt engineering, Retrieval-Augmented Generation (RAG) architectures, vector stores, and API integrations make you light up inside? If so, we want to hear from you! At 1st Central , we're on an exciting journey with AI … develop AI and Generative AI solutions using services like Azure OpenAI and Azure Cognitive Services Implement prompt engineering techniques and Retrieval-Augmented Generation (RAG) architectures. Ensure scalability, security, auditability, and efficiency of AI solutions through detailed system design and development practices. Deploy and manage AI solutions via CI/CD pipelines in Azure DevOps … deploying, and managing production-grade AI and Generative AI systems. Extensive experience with Cloud-based AI and Cognitive Services, and Retrieval-Augmented Generation (RAG) architectures. Deep expertise in API integration, preferably within the Azure ecosystem. Experience with Infrastructure as Code (IaC) across development, testing, and production environments. Solid understanding of Azure networking principles, security More ❯

Experience working in cloud environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What We Offer More ❯

environments (Azure preferred), including Azure Functions, APIM, Azure AI Foundry, Resource Groups, Azure Storage Accounts, App Insights, Key Vault, etc. GenAI Application Development - Experience in building GenAI applications with RAG, prompt/context engineering, embeddings, chat completions, and calling LLM APIs. Agentic AI Expertise - Strong understanding of agentic AI architecture, including LLMs, MCP, agent hierarchies, orchestration, evaluations, memory and trace More ❯

working with a small, agile team focused on deploying open-source models into production environments.?? Key Responsibilities Fine-tune and evaluate LLMs for domain-specific tasks Build and optimise RAG pipelines using vector databases Develop prompt engineering strategies and orchestration flows Integrate models into backend services via APIs Implement evaluation frameworks for response quality and reliability Essential Skills Strong Python More ❯

systems and significantly impact the direction of a successful early-stage business. Role Overview: Key Responsibilities: AI Software Development: Develop and enhance the company's AI-based (LLM/RAG) software. System Integration: Integrate offline versions of the software into customer systems. Backend Development: Work primarily with Python to build scalable backend systems and APIs. Minimum Qualifications & Experience: Backend Proficiency More ❯

data team and creating a culture that enables growth, development and psychological safety Exploring and applying Large Language Models (LLMs) and other modern AI techniques (e.g., embeddings, retrieval-augmented generation, summarisation) to enhance internal tools, automate workflows, or develop client-facing features Acquiring, cleaning, and integrating data from internal and external sources to enrich More ❯

data team and creating a culture that enables growth, development and psychological safety Exploring and applying Large Language Models (LLMs) and other modern AI techniques (e.g., embeddings, retrieval-augmented generation, summarisation) to enhance internal tools, automate workflows, or develop client-facing features Acquiring, cleaning, and integrating data from internal and external sources to enrich More ❯