6 of 6 Remote/Hybrid Permanent Weaviate Jobs

Gemini as well as self-hosted LLMs along with MCP integrations Implement Retrieval-Augmented Generation (RAG) techniques leveraging vector databases (Pinecone/ChromaDB/Weaviate/pgvector/etc), search engines such as ElasticSearch/Solr using both TF/IDF BM25 based full text search as well as similarity ...

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, CloudFormation ...

orchestration, memory, evaluation, and observability. Pioneer RAG & Multi-Modal Solutions Implement advanced Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone and Weaviate . Build multi-modal workflows spanning text, voice, and video, with a strong focus on accuracy, explainability, and performance. Design data ingestion and enrichment pipelines ...

Gemini . Implement RAG Pipelines Support the design and delivery of Retrieval-Augmented Generation (RAG) solutions using vector databases such as Pinecone or Weaviate . Develop Production-Ready Services Write clean, maintainable code in Python and/or JavaScript , contributing to microservices and APIs that meet performance, security, and reliability ...

orchestration 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 ...

orchestration 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 ...