1 to 25 of 29 Weaviate Jobs

Python development skills with experience building REST APIs, microservices, and scalable backend applications. Practical experience implementing RAG architectures using vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or FAISS. Understanding of software engineering best practices including Git, CI/CD, testing, code reviews, and cloud platforms such as AWS, Azure ...

/unsupervised ML and AI observability Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS). Experience in designing and scaling GenAI chatbots. Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration ...

Azure, AWS or GCP, alongside CI/CD, Docker, Kubernetes and Infrastructure as Code. Experience with vector databases and search technologies such as Pinecone, Weaviate or Azure AI Search. Strong understanding of AI governance, security, privacy and responsible AI principles. Comfortable working in client-facing environments and communicating effectively with ...

including 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 ...

effectively with technical and non-technical stakeholders.DesirableExperience with workflow automation platforms such as n8n, Power Automate, Dify or similar.Knowledge of vector databases including Pinecone, Weaviate, Chroma, FAISS or Milvus.Experience building Retrieval Augmented Generation (RAG) solutions.Understanding of AI governance, Responsible AI and AI security principles.Exposure to MLOps, model deployment and monitoring ...

effectively with technical and non-technical stakeholders.DesirableExperience with workflow automation platforms such as n8n, Power Automate, Dify or similar.Knowledge of vector databases including Pinecone, Weaviate, Chroma, FAISS or Milvus.Experience building Retrieval Augmented Generation (RAG) solutions.Understanding of AI governance, Responsible AI and AI security principles.Exposure to MLOps, model deployment and monitoring ...

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 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 ...

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 ...

hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel).Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that feed ...

hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI).Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic frameworks (LangChain, LangGraph, Semantic Kernel).Data pipelines: data lake/lakehouse architectures, ETL/ELT, and data quality/lineage tooling that feed ...

degree in Computer Science, Data Science, or related fieldNice to haveExperience with Azure AI Agent Service or Microsoft Agent FrameworkFamiliarity with vector databases (Pinecone, Weaviate, Qdrant, Milvus)Knowledge of AI safety techniques such as guardrails, bias mitigation, and model explainabilityUnderstanding of Intelligent Document Processing, data lineage, and distributed memory ...

Azure AI Foundry or Microsoft Agent FrameworkKnowledge of MCP and A2A protocols for agent and tool interoperabilityHands-on work with vector databases like Pinecone, Weaviate, Qdrant or pgvectorFamiliarity with distributed systems, workflow engines (Temporal, Airflow or Dagster) and event-driven architecturesExperience with open-source LLMs or Small Language Models ...

Senior Developer Has breadth of experience across different tech-stacks, such as JavaScript/TypeScript, Java, C#, or Python, amongst others Experienced in RAG Weaviate, OpenAI, Agents, MCP, Langchain, Prompt Engineering, Browser-Use, and Django Experienced building AI Tools, Agents and Agentic workflows (LangGraph, CrwAI) Hands-on Product building experience ...

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

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

integrating with enterprise systems (REST, Python, SQL, GraphQL, Webhooks etc). Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow Orchestration (LangChain, LangGraph, CrewAI) Knowledge of SLM Finetuning and Distillation is big advantage. Experience and knowledge ...

evaluation of LLM-based outputs Frameworks and orchestration LangChain LangGraph CrewAI Models and platforms OpenAI and/or Azure OpenAI Vector search and retrieval Weaviate or equivalent vector database technology Data and model support selecting and preparing data for AI-enabled solutions evaluating model or workflow outputs identifying opportunities ...

consistently 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 … Kernel, CrewAI, 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 ...

deployments, CI/CD, and MLOps tooling (MLFlow, Airflow)Nice to haveExperience with Microsoft Agent Framework, Azure AI Agent ServiceKnowledge of vector databases (Pinecone, Weaviate, Qdrant, Milvus)Familiarity with guardrail and AI safety techniques (output filtering, prompt injection defense)Experience in distributed systems, event-driven architectures, and workflow enginesPrior involvement ...

organizations. Preferred QualificationsFamiliarity with AI ecosystems such as LangGraph, Semantic Kernel, OpenAI, Azure OpenAI, or Anthropic, and/or vector stores such as Pinecone, Weaviate, OpenSearch, or PostgreSQL pgvector. Experience building AI-powered applications in regulated industries, including financial services or trading environments. Knowledge of enterprise architecture frameworks, governance models ...

move quickly while maintaining code quality, test coverage, and operational excellence. Preferred: Familiarity with AI/ML tools such as LangGraph, Haystack, Hugging Face, Weaviate, or similar ecosystems. Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them. Exposure to working with unstructured data (documents ...

working with Generative AI and ML infrastructure, including: Fine-tuning transformer models Managing embeddings Building RAG pipelines Familiarity with vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic search techniques. Strong foundation in cloud infrastructure, networking, security, CI/CD pipelines, and observability. Experience with cloud platforms (AWS, GCP, etc. ...

delivery: Hands-on RAG systems built and shipped recently - current work, not an old proof of concept Vector databases (e.g. pgvector, OpenSearch, Qdrant, Weaviate), embeddings, hybrid search and reranking Experience evaluating RAG systems properly (e.g. recall@k, faithfulness) Streaming platforms such as Kafka Agentic or multi-hop retrieval, GraphRAG, query ...