101 to 125 of 180 Permanent Weaviate Jobs

tools/functions callable by AI agents (tool schemas, function calling, structured outputs). Experience with retrieval-augmented generation (RAG) : vector databases (e.g., Pinecone, Weaviate, pgvector), embeddings, and chunking strategies. Working knowledge of prompt engineering and evaluation techniques for agent reliability, safety, and cost control. Familiarity with orchestrating multi-agent ...

software engineering, solutions engineering, or ML deployment roleProficiency in Python and working knowledge of AI/ML frameworks (e.g. OpenAI, Hugging Face, LangChain, Pinecone, Weaviate, etc.)Familiarity with building LLM applications, RAG systems, or conversational AI workflowsExperience integrating with enterprise systems via APIs or middleware (e.g. Salesforce, ServiceNow, SAP, Oracle ...

optimize workflows leveraging LLMs, embeddings, RAG systems, and vector databases. Integrate AI/ML libraries and external APIs (e.g., OpenAI, Hugging Face, LangChain, Pinecone, Weaviate). Experiment with prompt engineering and fine-tuning to improve reliability and performance of deployed agents. Collaboration & Delivery Partner with product and core engineering teams ...

optimize workflows leveraging LLMs, embeddings, RAG systems, and vector databases. Integrate AI/ML libraries and external APIs (e.g., OpenAI, Hugging Face, LangChain, Pinecone, Weaviate). Experiment with prompt engineering and fine-tuning to improve reliability and performance of deployed agents. Collaboration & Delivery Partner with product and core engineering teams ...

through caching, batching, and token monitoring Integrations & Data Services Data Pipeline Ownership: Implement and maintain RAG pipelines and integrations with vector databases (e.g., Pinecone, Weaviate, FAISS) Telemetry Integration: Ensure all backend services support LangSmith-based evaluation and comprehensive observability Security & Reliability Tenant Isolation: Implement RBAC, API authentication, and multi-tenant ...

development on Azure Experience building and consuming RESTful APIs; understanding of microservice and event-driven architectures Familiarity with vector databases (Azure AI Search, Qdrant, Weaviate) Experience with Azure DevOps or GitHub Actions for CI/CD A mindset that balances delivery speed with reusability - you look for ways to turn ...

similar tools for building multi-step, multi-agent AI workflows. Working knowledge of retrieval-augmented generation (RAG) patterns, vector databases (e.g., Pinecone, ChromaDB, Weaviate, pgvector), and embedding models. Experience with LLM APIs and platforms including OpenAI, Anthropic Claude, Google Gemini, and/or open-source models via Hugging Face ...

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 ...

fine‐tuning, or serving embedding models (e.g. sentence‐transformers, bi‐encoders, cross‐encoders), with practical experience setting up and managing vector databases (e.g. Qdrant, Weaviate, Milvus, pgvector) along with understanding trade‐offs e.g. when to use sparse or dense embeddings (or both) etc. Classical NLP training and evaluating text classifiers ...

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 science ...

/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 the foundation‐model contract ...

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 ...

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. You’re comfortable taking ...

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. You’re comfortable taking ...

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. You’re comfortable taking ...

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. You’re comfortable taking ...

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. You’re comfortable taking ...

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/CloudFormation … 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/ ...

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, professional ...

exposure data Familiarity with industry content and identity schemas: EIDR, Schema.org VideoObject, DDEX, or equivalent Experience with embedding models, vector databases (Milvus, Pinecone, Weaviate), and GraphRAG architectures (LangChain/LlamaIndex) Familiarity with GNN-based approaches to knowledge graph reasoning or entity resolution a plus Working knowledge of PySpark and Databricks ...

exposure data Familiarity with industry content and identity schemas: EIDR, Schema.org VideoObject, DDEX, or equivalent Experience with embedding models, vector databases (Milvus, Pinecone, Weaviate), and GraphRAG architectures (LangChain/LlamaIndex) Familiarity with GNN-based approaches to knowledge graph reasoning or entity resolution a plus Working knowledge of PySpark and Databricks ...

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 CX design … 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 ...

Job Description Job DescriptionJob Description Applied AI Engineer, Work From Home We are looking for an Applied AI Engineer to design, build, and optimize AI-powered features that sit directly inside our product workflows. The ...

Job Description Job DescriptionJob Description Applied AI Engineer, Work From Home We are looking for an Applied AI Engineer to design, build, and optimize AI-powered features that sit directly inside our product workflows. The ...

Job Description Job DescriptionJob Description Applied AI Engineer, Work From Home We are looking for an Applied AI Engineer to design, build, and optimize AI-powered features that sit directly inside our product workflows. The ...