51 to 72 of 72 Pinecone Jobs

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 ...

large‐scale deployments.Hybrid cloud or cloud‐adjacent patterns (Kubernetes CSI, cloud‐native fabrics, data locality).Experience with one or more vector databases (Milvus, Qdrant, Pinecone, pgVector, OpenSearch/Elasticsearch vectors, etc.), including schema design, ingestion, and operations.Solid understanding of RAG and Generative AI workflows: embeddings, retrieval, reranking, prompt design, context ...

working with AI tools and prompting. An understanding of point in time data is a strong plus Also desirable: experience with vector databases (pgvector, Pinecone, Weaviate, Qdrant or similar); machine learning experience (PyTorch, TensorFlow, XGBoost/LightGBM) for building, maintaining and extending existing models; Bloomberg API integration to Python; data ...

Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative fieldHands-on experience with cloud-native ML infrastructure platformsKnowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding modelsExperience with model serving frameworks (vLLM, TensorRT, Ray)Experience with A/B testing and experimentation frameworks for AI featuresContributions to open ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

databases, and business logic to AI models in a standardized, secure way Experience with databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, Redis), and vector databases (Pinecone, ChromaDB, Weaviate, or Qdrant). Strong understanding of software architecture, design patterns, and API design. Soft skills You lead with ownership and direction. ...

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 ...

dynamics; Demonstrable right to work in the United Kingdom. Desirable Experience designing and deploying RAG (Retrieval‐Augmented Generation) architectures and working with vector databases (Pinecone, Weaviate, Chroma, or similar); Familiarity with enterprise SaaS ecosystems: CRM (Salesforce, HubSpot), ERP, HRIS, marketing platforms, and their API surfaces; Prior experience in a consulting ...

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 ...

operating knowledge graphs or graph databases (e.g., Jena Fuseki, Neo4j, Amazon Neptune or equivalent). Experience with vector databases and embedding pipelines (e.g., Pinecone, Weaviate, Qdrant, pgvector). Practical experience implementing RAG architectures or LLM‐integrated data pipelines. Familiarity with semantic web standards — JSON‐LD, RDF, OWL, or SKOS. Strong ...

infrastructureExperience building and operating knowledge graphs or graph databases (e.g. Jena Fuseki, Neo4j, AmazonNeptune, or equivalent)Experience with vector databases and embedding pipelines (e.g. Pinecone, Weaviate, Qdrant, pgvector)Practical experience implementing RAG architectures or LLM-integrated data pipelinesFamiliarity with semantic web standards — JSON-LD, RDF, OWL, or SKOSStrong Python skills ...

high-performance APIs and caching strategies enabling low‐latency data access for AI agents and orchestration systems. Implement vector-based data retrieval layers (pgVector, Pinecone) and ensure efficient embedding pipelines for AI contexts. Partner with AI teams to monitor data latency, cost efficiency, and observability metrics. Collaboration & Governance Partner with ...

LLMs and tooling (OpenAI/Anthropic/Llama, Hugging Face, LangChain/LlamaIndex, function and tool calling). Retrieval and vector databases (FAISS, pgvector, Pinecone, Weaviate, or similar), and hybrid retrieval that combines graph and vector. Cloud and containers (AWS/GCP/Azure), Docker/Kubernetes, IaC (Terraform/… multi-model (graph, document, key-value), AQL, graph algorithms, GraphRAG Models & SDKs:OpenAI, Anthropic, Meta Llama, Hugging Face Retrieval:graph traversal plus FAISS, pgvector, Pinecone, Weaviate; rerankers (ColBERT, cross-encoders) Pipelines & Orchestration:LangChain, LlamaIndex, Ray, Airflow MLOps & Evals:MLflow, Weights & Biases, Ragas, promptfoo, Great Expectations Serving & Infra:vLLM, TGI, FastAPI ...

models for complex reaction networks, define the semantic ontologies that let AI reason across different chemical data types, and design vector search (e.g. pgvector, Pinecone) for similarity lookups across large molecular sets. Design the telemetry pipeline. Specify streaming ingestion for high-frequency robot and sensor data, with zero loss ...

agents across client use cases Work across LangGraph, LangChain, Claude Code/Codex/Gemini and RAG pipelines Implement RAG and vector database solutions (Pinecone, Weaviate, LlamaIndex) Deploy across cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio Bridge CX and engineering Hold the full stack from … with: Agentic frameworks: LangGraph, LangChain, CrewAI, Agentforce or similar Foundation model providers: Claude Code/Codex/Gemini, OpenAI or AWS Bedrock Vector databases: Pinecone, Weaviate, LlamaIndex or pgvector Cloud platforms: AWS Bedrock, GCP Vertex AI or Azure AI Studio Leadership & consulting skills Clear communication; able to explain technical decisions ...

Author custom skills and slash commands for Claude Code to codify team‐specific workflows. Implement RAG pipelines and integrate vector stores (e.g., Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data. Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited. Apply AI‐specific … Model Context Protocol) for connecting agents to internal tools and data sources. Working knowledge of RAG patterns and vector store integration (e.g., Qdrant, pgvector, Pinecone). Awareness of AI‐specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions ...

agent loops.Author custom skills and slash commands for Claude Code to codify team-specific workflows.Implement RAG pipelines and integrate vector stores (e.g. Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data.Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited.Apply AI-specific risk controls … Model Context Protocol) for connecting agents to internal tools and data sources.Working knowledge of RAG patterns and vector store integration (e.g. Qdrant, pgvector, Pinecone).Awareness of AI-specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions).Why Signant ...

Author custom skills and slash commands for Claude Code to codify team-specific workflows. Implement RAG pipelines and integrate vector stores (e.g. Qdrant, pgvector, Pinecone) to ground agent outputs in trusted data. Instrument agents for evaluation and observability so their outputs can be verified, measured, and audited. Apply AI-specific … Model Context Protocol) for connecting agents to internal tools and data sources. Working knowledge of RAG patterns and vector store integration (e.g. Qdrant, pgvector, Pinecone).Awareness of AI-specific risk areas relevant to a regulated environment (OWASP LLM Top 10, hallucination/determinism concerns, and auditability of agent decisions).Why ...