and scaling multi-agent systems or tool-augmented LLM workflows. Familiarity with secure cloud development practices and IAM role design. Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). Exposure to contact centre automation, conversational agents, or RAG pipelines. Adecco is a disability-confident employer. It is important to us that we run an inclusive and More ❯
and scaling multi-agent systems or tool-augmented LLM workflows. · Familiarity with secure cloud development practices and IAM role design. · Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). · Exposure to contact centre automation, conversational agents, or RAG pipelines. Please click here to find out more about our Key Information Documents. Please note that the documents More ❯
or Azure proficiency Containers & IaC: Docker, Kubernetes, Docker Compose, Terraform Monitoring: Langsmith, Langfuse, or similar CI/CD: GitLab, GitHub, Jenkins Databases: SQL (PostgreSQL), NoSQL (MongoDB), vector DBs (ChromaDB, Pinecone, Qdrant, etc.) Professional Skills: Experience working in agile delivery environments Excellent communication and stakeholder management Demonstrated leadership in project delivery or team management Eligible for or holding active SC (Security More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Anson McCade
varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate More ❯
varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate More ❯
Cambridge, Cambridgeshire, England, United Kingdom Hybrid / WFH Options
Ascent Sourcing Ltd
Practical experience with memory frameworks like Mem0 or Letta. Understanding and production experience with traditional RAG and agentic RAG architectures. Strong grasp of embedding systems and vector databases (e.g., Pinecone, Weaviate, FAISS). Production experience with LiveKit or similar audio/video platforms. What You’ll Be Doing Building and deploying scalable AI features, agents, and services powered by LLMs. More ❯
Experience building with generative AI applications in production environments. Expertise with microservices architecture and RESTful APIs. Solid understanding of database technologies such as PostgreSQL and vector databases as Elastic, Pinecone, Weaviate, or similar. Familiarity with cloud platforms (AWS, GCP, etc.) and containerized environments (Docker, Kubernetes). You are committed to writing clean, maintainable, and scalable code, following best practices in More ❯
largescale transformer models (BERT, GPT) and promptengineering for sentiment tasks Background building activelearning and annotation pipelines to bootstrap training data Familiarity with semantic search or vector databases (Elasticsearch, FAISS, Pinecone) for topic modeling and similarity queries Familiarity with crypto markets, order books, and risk-management frameworks Familiarity with anomalydetection methods for streaming text and timeseries data Experience developing EVM smart More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
and reliability Essential Skills Strong Python skills and experience with Hugging Face Transformers Familiarity with LLM fine-tuning and inference optimisation Experience with vector search and embeddings (e.g. FAISS, Pinecone) Understanding of prompt engineering and few-shot learning Ability to work independently in a hybrid, agile environment Nice to Have Experience with LangChain, LlamaIndex, or similar orchestration tools Exposure to More ❯
prompts for LLMs (OpenAI, Claude, etc.) Building prompt libraries and evaluation frameworks Structuring unstructured data (PDFs, notes, forms) into usable formats Working with RAG pipelines and vector databases (FAISS, Pinecone, etc.) Embedding LLMs into user-facing healthcare tools (e.g., AI assistants, in-context help) Collaborating with product, design, and clinical teams to ship real features What You’ll Bring Experience More ❯
Data Factory, Azure Synapse, and Azure Functions. Implementing modern retrieval techniques such as vector search, semantic search and Retrieval-Augmented Generation (RAG) using tools like Azure Cognitive Search, FAISS, Pinecone, or Weaviate. Familiarity with data governance, privacy, and ethical AI principles. Experience with DevOps tools and practices, including CI/CD pipelines, infrastructure as code and monitoring. Applied knowledge of More ❯
rapid, iterative cycles with weekly releases Prompt Engineering: Able to craft, test, and refine prompts for outputs like chat, image, or video LLM + Vector Tools: Experience with embeddings, Pinecone/Weaviate, and building RAG-style pipelines Why Join Magic Group? No red tape. Just build, launch, and scale A small, senior team with high trust and even higher impact More ❯
prompt tweaks changed an LLM's output to match a specific product need. Nice-to-Haves LangChain, LlamaIndex, or any RAG experiment on your GitHub. Vector database dabbling (pgvector, Pinecone). A side project people outside your family have used. Our Stack React 18 Next.js Node 20 FastAPI OpenAI & Anthropic APIs Postgres + pgvector Vercel Fly.io GitHub Actions Cursor & Windsurf More ❯
