16 of 16 Pinecone Jobs in the City of London

Anthropic Claude, Azure OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including ...

MLOps/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 ...

MLOps/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 ...

findings 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 ...

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/ ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

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 ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

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 ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

Write 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 ...

/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. ...

confidence using popular machine learning libraries such as PyTorch, TensorFlow, or scikit-learn Familiarity with vector-based storage and search systems (e.g. pgvector, Pinecone, Azure Search), as well as experience working with graph technologies like Neo4j Practical understanding of retrieval-augmented generation pipelines and how to implement structured outputs ...

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/… interest in 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 ...

Collaborate with AI, Product, and Engineering teams to operationalise agentic workflows . Develop APIs and interfaces for semantic and vector-based data operations (e.g. Pinecone, PostgreSQL). Implement monitoring, logging, and compliance measures aligned with ISO 27001/SOC2 standards. Continuously evaluate new tools and frameworks in the data … pipeline and service development. Proficiency with AWS (Lambda, S3, Glue) and orchestration tools (Airflow, Dagster, etc.). Familiarity with relational and vector databases (PostgreSQL, Pinecone, MySQL). Understanding of API development and event-driven architectures. A mindset that’s curious, collaborative, and driven by innovation and automation . What ...