12 of 12 Weaviate Jobs in the City of London

/LLMOps pipelines, and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.). Experience in architecting and scaling GenAI chatbots Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI ...

curate training datasets (structured/unstructured text, images, code). Apply data preprocessing, tokenization, and embedding generation techniques. Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. Partner with business stakeholders to identify and shape impactful AI use cases. Contribute to the development ...

/LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.). Ability to design enterprise-level AI/Gen AI platform/solutions with the client’s existing enterprise stack. Hands-on mastery ...

production-ready code (Python/TypeScript), manage CI/CD pipelines, and ensure scalable deployment via Docker and Kubernetes Infrastructure: Manage Vector Databases (Pinecone, Weaviate, Chroma) and ML model registries Experience: Experience: 3-5 years of professional engineering experience Core ML & Data Science: Proven experience applying traditional ML techniques (Random ...

production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience in full stack development and AI/ ...

production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g., Pinecone, Weaviate, FAISS). Proven experience in full stack development and AI/ML system implementation within enterprise environments. Strong grasp of advanced techniques such as complex ...

clearly. Eligible for DV security clearance; no sponsorship provided. Desirable: Advanced LLM techniques: agents, tool use, and agentic workflows. Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications. Experience with feature stores (Feast, AWS Feature Store). Containerisation (Docker) and orchestration (Kubernetes, ECS). Infrastructure as Code (Terraform, CloudFormation ...

Help You With Them • Experience with advanced LLM techniques: agents, tool use, and agentic workflows • Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications • Experience with feature stores (Feast, AWS Feature Store) • Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) • Familiarity with Infrastructure as Code (Terraform, CloudFormation) • Experience with ...

agent frameworks. Skilled in prompt engineering , integrating foundation model APIs, and LLM fine-tuning techniques. Expertise in building RAG systems , vector databases (e.g., Pinecone, Weaviate), and embedding pipelines. Experience with ML/LLMOps for monitoring, evaluation, and traceability. Solid understanding of distributed systems , microservices, and real-time data processing. Comfortable ...

APIs (OpenAI, Anthropic, Cohere) and cutting-edge open-source AI frameworks (LangChain, LlamaIndex) Design and optimise RAG pipelines leveraging embeddings and vector databases (Pinecone, Weaviate, FAISS) Develop advanced agentic workflows and harness knowledge graphs for smarter automation What we're looking for: Backend engineer with deep interest in practical ...

APIs (OpenAI, Anthropic, Cohere) and open-source AI frameworks (LangChain, LlamaIndex, LangGraph) into production Design and optimise RAG pipelines using embeddings, vector databases (Pinecone, Weaviate, FAISS) and other retrieval systems Work with knowledge graphs and structured data to add richer context and smarter reasoning to AI workflows Develop agentic/… practical, product-focused AI integration Experience building semantic search, RAG pipelines or similar retrieval-heavy AI systems Hands-on with vector databases (Pinecone, Weaviate, FAISS or similar) and large, complex datasets Familiarity with LLM tooling (e.g. LangChain, LlamaIndex) and agentic AI concepts Comfortable in modern backend stacks (Node.js, Python ...

cost. Design and run cloud-native AI services across AWS and Databricks, including ingestion and embedding pipelines. Scale and operate vector search infrastructure (Weaviate, OpenSearch, Algolia, AWS Bedrock Knowledge Bases). Implement strong observability, CI/CD, security, and governance across AI workloads. Enable future architectures such as multi-model … large-scale data or embedding pipelines. Proven experience building and operating production AI systems , including RAG pipelines, LLM-backed services, and vector search (Weaviate, OpenSearch, Algolia). Proficiency in Python , with experience deploying containerised services on Kubernetes using Terraform . Solid understanding of distributed systems, cloud architecture, and API design ...