18 of 18 Pinecone Jobs in the South East

unsupervised) MLOps/LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ ...

Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral APIs LLM Frameworks: LangChain, LlamaIndex for building LLM-powered applications Vector Databases: FAISS, Weaviate, Pinecone, Qdrant (Nice-to-Have) Retrieval-Augmented Generation (RAG): Experience building hybrid systems combining LLMs with enterprise data MLOps & Infrastructure MLOps: Model versioning, monitoring, logging Bias ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines (e.g., Azure AI Search, Pinecone) and guardrails for GenAI. Background in enterprise architecture and integration patterns (event-driven, REST, GraphQL). Relevant certifications such as Agile/Scrum (PSM/ ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Vector Databases: Experience with and (but not limited to) ChromaDB, Pinecone, PGVector, MongoDB , Qdrant etc. NoSQL: Familiarity with NoSQL databases (e.g., MongoDB preferred). SQL: Experience working with SQL databases like PostgreSQL. Proficient in Git and version ...

OpenAI, Anthropic, or similar). Expertise in GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face Transformers). Hands-on experience with RAG pipelines, vector databases (Pinecone, FAISS, Weaviate), and chatbot deployment. Proven experience with agentic AI (tool use, planning, multi-step reasoning) and production-level systems. Experience delivering AI solutions ...

LangGraph, LangSmith or similar Solid NLP background (tokenisation, embeddings, transformers, BERT-style models, sentiment analysis) Experience integrating vector databases (e.g. Azure AI Search, OpenSearch, Pinecone, Weaviate) Cloud experience on Azure, AWS or GCP Familiarity with MLflow, model evaluation frameworks, observability & monitoring Strong understanding of deploying AI systems into real-world ...

similar foundation models- Prompt engineering and chain-of-thought reasoning RAG & Knowledge Systems:- Retrieval-Augmented Generation (RAG) pipeline implementation- Vector database experience (CockroachDB, Pinecone, or similar)- Embedding model selection and optimisation- Semantic search and similarity matching- Context window management and chunking strategies MCP & Tool Integration:- Model Context Protocol (MCP) implementation ...

researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and shape … Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure, Transformers, Reinforcement Learning, Vector Databases, Pinecone, Weaviate, Semantic Search, API Development, AI Deployment, Model Serving, AI Automation, Early Stage Startup, AI Startups, Tech Startup, Machine Intelligence, Applied AI, AI Applications ...

retrieval systems with large language models. Build and maintain applications using LangChain to orchestrate complex AI workflows. Implement and manage vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus) for fast similarity search and retrieval. Develop embedding pipelines for unstructured data using models like Sentence Transformers, OpenAI, or Hugging Face. Collaborate with … Experience with large language models (GPT, BERT, etc.). Fine-tuning and prompt engineering. Experience with vector similarity search. Knowledge of popular vector DBs: Pinecone, Weaviate, FAISS, Vespa, Milvus. Generating and managing embeddings (using models like SentenceTransformers, OpenAI, Hugging Face). Familiarity with LangChain for building LLM-powered applications. Ability ...