1 to 25 of 33 Permanent pgvector Jobs

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI framework Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI framework Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI framework Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI framework Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

Snowflake, AWS S3, RDS, EBS, or Glacier Experience with vector databases, embeddings, and their affiliated data structures, file formats, services, APIs, etc (e.g. FAISS, PGVector, OpenSearch/Elasticsearch, Hugging face with Pinecone, Bedrock Knowledge Base) Experience in generative AI, working with LLMs, adding tool calls (MCP) and agents (A2A). ...

Snowflake, AWS S3, RDS, EBS, or Glacier Experience with vector databases, embeddings, and their affiliated data structures, file formats, services, APIs, etc (e.g. FAISS, PGVector, OpenSearch/Elasticsearch, Hugging face with Pinecone, Bedrock Knowledge Base) Experience in generative AI, working with LLMs, adding tool calls (MCP) and agents (A2A). ...

Snowflake, AWS S3, RDS, EBS, or Glacier Experience with vector databases, embeddings, and their affiliated data structures, file formats, services, APIs, etc (e.g. FAISS, PGVector, OpenSearch/Elasticsearch, Hugging face with Pinecone, Bedrock Knowledge Base) Experience in generative AI, working with LLMs, adding tool calls (MCP) and agents (A2A). ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI frameworks Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI frameworks Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

OpenAI, Anthropic, Mistral, Llama and similar LLMs Use LangChain, LangGraph, CrewAI or similar AI frameworks Work with vector databases including Pinecone, Qdrant, ChromaDB and PGVector Take GenAI POCs into production and scale them Build APIs, microservices and AI integrations Deploy solutions using AWS/Azure, Docker and Kubernetes Write clean ...

Azure OpenAI, AWS Bedrock, OpenAI API, or open-source models such as Llama and Mistral.Experience with vector databases and embedding workflows, including Chroma, Weaviate, pgvector, Azure AI Search, or equivalent.Solid understanding of CI/CD pipelines for application code and ML/AI artifacts, including MLflow, DVC, or equivalent.Strong container ...

including GitHub, GitLab, Jenkins, or similar.Familiarity with monitoring and observability tools for AI applications and services.Database TechnologiesExperience 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 ControlStrong experience using Git and modern version control platforms.Working ...

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 ...

pipelines through Azure ML, AWS SageMaker, Vertex AI, Databricks, or Modal/Fly.io for lightweight LLM deployment. Utilize vector databases (Pinecone, Weaviate, Milvus, ChromaDB, pgVector) and embedding stores. Use AI-powered dev tools (GitHub Copilot, Cursor, Codeium, Aider, Windsurf) to accelerate iteration. Implement LLMOps/PromptOps using: Weights & Biases, MLflow ...

experimental projectsStrong Docker, Kubernetes/OpenShift, CI/CD and pytest knowledgeExperience working with large codebases and improving existing services safelyKnowledge of Azure, RAG, pgvector, Chroma, FAISS, Entra ID, OAuth/OIDC, Redis, Terraform, Prometheus or OpenTelemetry would strengthen your application. Current or recently held SC clearance is required. ...

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 to non-engineers Collaborative ...

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 CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines ...

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 CI/CD for AI: version-controlled prompts, automated testing, deployment pipelines ...

help you with them: Experience with 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) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with ...

well help you with them: Experience with 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) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience ...

help you with them: Experience with 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) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with ...

across teams.• Retrieval-Augmented Generation (RAG) & Knowledge Architecture: Expertise architecting RAG and knowledge-grounded systems—chunking strategies, embeddings, vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and retrieval evaluation. Familiarity with advanced patterns such as GraphRAG and agentic RAG to maximize factual grounding and minimize hallucination … AutoGen). Experience with cloud AI platforms (e.g., Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI), vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), containerization and orchestration (Docker, Kubernetes), and distributed computing is advantageous.• Architecture Design: Ability to design end-to-end Generative and Agentic AI architectures that ...

practices. Experience and Skills (Nice to have)· Previous experience building a user-facing GenAI/LLM software application· Previous experience with vectors and embeddings (pgvector, chromadb)· Knowledge of LLM RAG/Agent core concepts and fundamentals· Experience with Neo4J, GraphQL for efficient data querying for APIs,· CI/CD tools ...

help you with them: Experience with advanced LLM techniques: agents, tool use, and agentic workflowsExperience with vector databases (Pinecone, Weaviate, pgvector) for RAG applicationsExperience with feature stores (Feast, AWS Feature Store)Experience with containerisation (Docker) and orchestration (Kubernetes, ECS)Familiarity with Infrastructure as Code (Terraform, CloudFormation)Experience with data processing ...

native SDKs; sandboxing, permissioning, and human-in-the-loop design Retrieval and knowledge: RAG and Graph RAG at enterprise scale; vector and hybrid search (pgvector, OpenSearch/Elasticsearch, or dedicated stores) including chunking strategy, reranking, and distributed retrieval; knowledge graphs and entity resolution; Text-to-SQL over complex enterprise schemas ...