11 of 11 Permanent Pinecone Jobs in London

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate More ❯

varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate More ❯

Experience building with generative AI applications in production environments. Expertise with microservices architecture and RESTful APIs. Solid understanding of database technologies such as PostgreSQL and vector databases as Elastic, Pinecone, Weaviate, or similar. Familiarity with cloud platforms (AWS, GCP, etc.) and containerized environments (Docker, Kubernetes). You are committed to writing clean, maintainable, and scalable code, following best practices in More ❯

largescale transformer models (BERT, GPT) and promptengineering for sentiment tasks Background building activelearning and annotation pipelines to bootstrap training data Familiarity with semantic search or vector databases (Elasticsearch, FAISS, Pinecone) for topic modeling and similarity queries Familiarity with crypto markets, order books, and risk-management frameworks Familiarity with anomalydetection methods for streaming text and timeseries data Experience developing EVM smart More ❯

scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to adeeb.rahman@opusrs.com More ❯

scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to adeeb.rahman@opusrs.com More ❯

scaling LLMs for real-world applications. Key Skills: Strong Python engineering background Experience with LLMs (e.g. Hugging Face, OpenAI, LangChain) Model fine-tuning, RAG pipelines, vector databases (e.g. FAISS, Pinecone) Cloud (AWS/GCP), CI/CD, Docker Bonus: Knowledge of model optimization, quantization, or open-source contributions. 📩 If interested send your CV to adeeb.rahman@opusrs.com More ❯

rapid, iterative cycles with weekly releases Prompt Engineering: Able to craft, test, and refine prompts for outputs like chat, image, or video LLM + Vector Tools: Experience with embeddings, Pinecone/Weaviate, and building RAG-style pipelines Why Join Magic Group? No red tape. Just build, launch, and scale A small, senior team with high trust and even higher impact More ❯

prompt tweaks changed an LLM's output to match a specific product need. Nice-to-Haves LangChain, LlamaIndex, or any RAG experiment on your GitHub. Vector database dabbling (pgvector, Pinecone). A side project people outside your family have used. Our Stack React 18 Next.js Node 20 FastAPI OpenAI & Anthropic APIs Postgres + pgvector Vercel Fly.io GitHub Actions Cursor & Windsurf More ❯

controllers. Develop and maintain AI microservices using Docker, Kubernetes, and FastAPI, ensuring smooth model serving and error handling; Vector Search & Retrieval: Implement retrieval-augmented workflows: ingest documents, index embeddings (Pinecone, FAISS, Weaviate), and build similarity search features. Rapid Prototyping: Create interactive AI demos and proofs-of-concept with Streamlit, Gradio, or Next.js for stakeholder feedback; MLOps & Deployment: Implement CI/… experience fine-tuning LLMs via OpenAI, HuggingFace or similar APIs; Strong proficiency in Python; Deep expertise in prompt engineering and tooling like LangChain or LlamaIndex; Proficiency with vector databases (Pinecone, FAISS, Weaviate) and document embedding pipelines; Proven rapid-prototyping skills using Streamlit or equivalent frameworks for UI demos. Familiarity with containerization (Docker) and at least one orchestration/deployment platform More ❯

the squad with a senior engineer who can deliver robust product features and help us responsibly weave AI (LLMs, RAG) into the user experiencealongside peers who already experiment with Pinecone, LangChain and VertexAI. As a senior fullstack engineer you will design, build and operate userfacing features endtoendUI components, APIs, data models and infrawhile mentoring teammates and shaping architecture. Roughly … Next.js, NestJS and PostgreSQL. Architecture stewardship Drive RFCs, enforce TypeScript standards, improve CI/CD and observability. AI integration (as needed) Prototype and productionise LLM/RAG components (VertexAI, Pinecone, LangChain) when they add clear value; own evaluation metrics and cost monitoring. Quality & performance Champion automated testing, accessibility and webperformance budgets. Mentorship & collaboration Pair program, run knowledgeshare sessions and provide … measurable impact and clean, maintainable code. Are comfortable with GDPR, ISO27001 and privacybydesign principles. Let us know if you have Experience integrating LLM services (VertexAI, OpenAI) and vector DBs (Pinecone). Implemented feature flagging & A/B experimentation. Worked on accessibility, localisation or performancecritical projects. Background in information retrieval or search relevance. This likely wont be the right role if More ❯