1 to 25 of 26 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 ...

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 ...

Role: Design and build end-to-end Gen AI pipelines using LLMs (Open AI, Azure Open AI, Anthropic) Develop RAG architectures with vector databases (Pinecone, FAISS, Azure AI Search) Optimize LLM outputs using prompt engineering, embeddings, and evaluation techniques Build AI solutions for document processing, compliance, and banking chatbots Develop ...

Architect Strong expertise in: Generative AI & LLMs, RAG (Retrieval-Augmented Generation), Agentic AI frameworks Hands-on with; LLMs (OpenAI, Llama, Claude, Mistral), Vector DBs (Pinecone, Weaviate, FAISS), Frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, LangGraph) Strong Python + ML frameworks (PyTorch/TensorFlow) Experience deploying on AWS, Azure, or GCP Experience leading ...

working in cloud environments (AWS, Azure, GCP, or Databricks) Familiarity with CI/CD pipelines and modern engineering practices Experience with vector databases (e.g. Pinecone, Chroma) Experience with agent frameworks (e.g. LangChain, LangGraph, or similar) Understanding of AI evaluation frameworks and production readiness Experience working in Agile delivery environments (Agile ...

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/ ...

frameworks (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face) Strong understanding of prompt engineering techniques and optimisation strategies Experience working with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) Practical experience with model evaluation, tuning, and performance optimisation Experience integrating AI solutions into APIs, microservices, and front-end applications Strong understanding ...

frameworks (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face) Strong understanding of prompt engineering techniques and optimisation strategies Experience working with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) Practical experience with model evaluation, tuning, and performance optimisation Experience integrating AI solutions into APIs, microservices, and front-end applications Strong understanding ...

Microservices Architecture Cloud platforms – AWS, Azure, or GCP Preferred Agentic framework experience – LangChain, LangGraph, AutoGen, or similar RAG pipeline design and vector database experience (Pinecone, Weaviate, pgvector) Agile/SDLC tooling – Jira, Git, CI/CD pipelines #J-18808-Ljbffr ...

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 ...

build complex, stateful, and cyclic agent architectures. Core Tech Stack: Strong proficiency in Python, framework integrations (LlamaIndex, Hugging Face), and vector databases (e.g., Pinecone, Qdrant, Milvus, Chroma). Software Fundamentals: Background in solid software engineering practices (Git, testing, design patterns, API development via FastAPI/Flask). Cloud Infrastructure: Experience ...

/indexing, hybrid search, grounding and hallucination mitigation. Applied AI/ML: hands-on with LLMs, embeddings and vector databases (FAISS/Milvus/Pinecone). LLMOps & evaluation: prompt pipelines, automated/offline evaluation, safety/guardrails, telemetry, versioning and CI/CD for ML. Cloud engineering: Azure (preferred ...

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 ...

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 ...

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 ...

architectures (graph‐augmented retrieval for grounded generation); Semantic layer and business intelligence platforms (Looker, dbt Semantic Layer, AtScale); Vector databases and hybrid retrieval (Qdrant, Pinecone, pgvector, AlloyDB vector search); Cloud data platforms at scale (BigQuery, Snowflake, Databricks, Spanner); Data cataloging and governance (Google Knowledge Catalog/Dataplex, Collibra, Alation, Atlan ...

architectures (graph-augmented retrieval for grounded generation)– Semantic layer and business intelligence platforms (Looker, dbt Semantic Layer, AtScale)– Vector databases and hybrid retrieval (Qdrant, Pinecone, pgvector, AlloyDB vector search)– Cloud data platforms at scale (BigQuery, Snowflake, Databricks, Spanner)– Data cataloging and governance (Google Knowledge Catalog/Dataplex, Collibra, Alation, Atlan ...

Stack Engineering: Python, TypeScript, React, APIs, Microservices, FastAPI. Cloud & DevOps: AWS/Azure, Docker, Kubernetes, Terraform, CI/CD. Data & Vector Search: PostgreSQL, MongoDB, Pinecone, Qdrant, ChromaDB, PGVector. Observability & Tooling: LangSmith, Langfuse, Git, GitHub, GitLab. Your Role: Collaborate with the team to develop GenAI proof-of-concepts (POCs) for clients … 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 ...