4 of 4 Retrieval-Augmented Generation Jobs in Lancashire

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 ❯

multi-step reasoning pipelines, and memory management using frameworks such as LangChain, CrewAI, and Autogen. Engineer and tune prompts to enhance the performance and reliability of generative tasks. Design RAG systems using vector databases like Pinecone, Chroma, and PosgreSQL for contextual retrieval. Incorporate semantic search and embedding strategies for more relevant and grounded LLM responses. Utilize Guardrails to implement applications … React for demoable outputs. Develop robust API integrations to connect AI agents with internal and external services and data sources. Use SQL to query structured databases and integrate with RAG or knowledge ingestion pipelines. Essential Skills Proficiency in Python programming. Experience in building multi-step intelligent systems. Knowledge of machine learning and artificial intelligence. Familiarity with frameworks like LangChain and More ❯

LangChain, CrewAI, and vector databases. Core Responsibilities Build and iterate on LLM/agent-based prototypes (e.g., copilots, chatbots, A2A agents). Implement multi-step reasoning, memory modules, and RAG pipelines. Use frameworks like LangChain, LangGraph, CrewAI, and tools like Pinecone, FAISS. Optimize performance and ensure responsible AI practices. Deploy via cloud platforms (AWS Bedrock, Azure AI, Google Vertex). More ❯

trajectory forecasted for 2025. Our platform is already trusted by nearly half of the top 50 financial institutions globally. The Technology At the core of our platform is a RAG-based architecture, purpose-built for finance. It’s designed to replicate the kind of deep reasoning you see in leading models like OpenAI’s o1—capable of parsing nuanced questions … frameworks (Python, React, TypeScript, etc.) and can build production-ready systems end-to-end Are excited by AI-native product design and have experience working with or around LLMs, RAG, or agent-like architectures Love talking to users and solving real business problems—not just coding in a vacuum Bring an entrepreneurial mindset, with an eye toward growing into a More ❯