1 to 25 of 32 Pinecone Jobs in the UK

Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate or ChromaDB Cloud & DevOps Experience with at least one major cloud platform: AWS (preferred) Bedrock SageMaker Lambda ECS/EKS S3 Or experience within ...

retrieval-augmented generation (RAG). Hands-on experience implementing GenAI solutions in production, including LLMs, prompt engineering, RAG architectures, LangChain, and vector databases (e.g., Pinecone, FAISS, Milvus). Proven hands on experience delivering and monitoring production grade AI/ML systems on cloud platforms such as AWS, GCP or Azure ...

LlamaIndex, and Hugging Face, including agentic and multi‐step workflows* **Proven experience designing and implementing Retrieval‐Augmented Generation (RAG) systems**, including vector databases (pgvector, Pinecone, Weaviate, FAISS, etc.) and advanced retrieval strategies (hybrid search, re‐ranking, metadata filtering)* **Strong understanding of prompt engineering, workflow design, and Gen‐AI optimization**, balancing ...

regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation ...

experience with AI system design, architecture, and distributed systems Expertise in API-based backend development (e.g. FastAPI or similar) Experience with vector databases (e.g. Pinecone, Chroma) Experience with agent frameworks (e.g. LangChain, LangGraph, or similar) Strong understanding of evaluation frameworks for AI/agent systems Experience implementing CI/ ...

operate, support, and secure mission-critical applications Previous experience deploying and managing LLM-model based applications and agents Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets Exposure to cloud-native microservices architecture Familiarity with advanced AI/ML concepts and protocols, including Retrieval ...

secure mission-critical applications \n Previous experience deploying and managing LLM-model based applications and agents \n Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets \n Exposure to cloud-native microservices architecture \n Familiarity with advanced AI/ML concepts and protocols, including ...

operate, support, and secure mission-critical applications \ NPrevious experience deploying and managing LLM-model based applications and agents\ NExposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets\ NExposure to cloud-native microservices architecture\ NFamiliarity with advanced AI/ML concepts and protocols, including Retrieval ...

embeddings, prompt engineering or fine tuning ·Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks ·Experience with vector databases such as Pinecone, Chroma or similar ·API development experience, ideally with FastAPI or similar frameworks ·Knowledge of MLOps, LLMOps, CI/CD or production deployment practices ·Experience designing ...

embeddings, prompt engineering or fine tuning · Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks · Experience with vector databases such as Pinecone, Chroma or similar · API development experience, ideally with FastAPI or similar frameworks · Knowledge of MLOps, LLMOps, CI/CD or production deployment practices · Experience designing ...

workflow orchestration using LangChain, CrewAI, AutoGen, ADK and LangGraph.\ NImplement Retrieval-Augmented Generation (RAG) pipelines and semantic search using vector databases such as Pinecone and Chroma, including indexing, retrieval policies, and evaluation.\ NBuild and integrate agent tools (MCP) and APIs to connect agents with external services, databases, and internal systems ...

Preferred\n\ N\n Agentic framework experience - LangChain, LangGraph, AutoGen, or similar\ N\n RAG pipeline design and vector database experience (Pinecone, Weaviate, pgvector)\ N\n Agile/SDLC tooling - Jira, Git, CI/CD pipelines\ N \n\nAt BNY, our culture allows us to run our company better ...

extraction, policy summarisation, intelligent routing — including evaluation, guardrails, cost, and latency considerations. Architect retrieval-augmented generation (RAG) solutions using vector-search platforms (e.g., OpenSearch, Pinecone), owning decisions on chunking, embeddings, retrieval quality, and context management. Champion fluent use of AI coding assistants (Claude Code, GitHub Copilot, Cursor, etc.) across ...

with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Database Management 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. Version Control: Proficient ...

GitLab, Jenkins, or similar. Familiarity with monitoring and observability tools for AI applications and services. Database Technologies Experience with vector databases such as ChromaDB, Pinecone, PGVector, Qdrant, MongoDB, or similar solutions. Familiarity with NoSQL databases. Experience working with SQL databases, particularly PostgreSQL or equivalent. Version Control Strong experience using ...

concepts and protocols, including Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP)\ N\n Exposure to vector stores such as Pinecone, GCP RAG engine, and AWS S3 Vector Buckets\ N\n Previous experience deploying and managing ML models\ N\n Experience working in highly regulated environments ...

DevSecOps practices. Set Yourself Apart... Cloud certifications (e.g. Azure Solutions Architect, Google Professional Cloud Architect). Exposure to MLOps frameworks and vector databases (e.g. Pinecone, Weaviate). Experience contributing to proof‐of‐concepts or MVPs, demonstrating rapid learning and experimentation. Experience supporting production AI/ML solutions, ideally within retail ...

Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field Hands-on experience with cloud-native ML infrastructure platforms Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Experience with A/B testing and experimentation frameworks for AI features ...

workflows Designing and maintaining backend services and APIs (primarily Python, FastAPI/Flask) Building and scaling data pipelines and search systems using: ElasticSearch, Weaviate, Pinecone, and other vector databases Engineering secure, containerised architectures using Docker and Kubernetes Ensuring high availability, fault tolerance, and performance for mission-critical workloads Providing technical ...

leveraging AI/GAI technologies and large language models (LLMs) Advanced AI Integration : Apply experience with retrieval-augmented generation (RAG), vector databases (e.g. Pinecone, Weaviate, FAISS), and enterprise search for AI-driven knowledge discovery Optimize AI Performance : Utilize practical experience designing structured prompts, fine-tuning models, and cost optimization strategies ...

MongoDB/DynamoDB) Experience with CI/CD, microservices, TDD/BDD. Knowledge of secure system design. Desirable (AI & Data) Vector DBs: Milvus, Weaviate, Pinecone Data orchestration: Airflow, Prefect, Dagster Search: ElasticSearch/OpenSearch AI frameworks: LangChain, Hugging Face MLOps: MLflow, Kubeflow If you are looking for an opportunity ...

Architect agent loops: planner/executor/verifier patterns, tool‐use schemas, retry + escalation logic. Build retrieval pipelines: chunking strategy, vector DB choice (Pinecone/pgvector/Weaviate), reranking, freshness handling. Stay current on Anthropic + OpenAI release notes; adjust prompts + schemas when APIs evolve. We treat ...

just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent opportunities ...

just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent opportunities ...

just prototypes Demonstrable experience of building and deploying complex AI applications using LLMs and ideally, agentic workflows A familiarity with vector databases (pgvector, ChromaDB, Pinecone or similar) is a plus Benefits include: Flexibility - the team works fully remotely, albeit with frequent meetups to share ideas Stock options Excellent opportunities ...