Weaviate

Ask HN: Who is hiring? (August 2026)

Hello! I’m interested in your Senior Fullstack Engineer position. I believe my experience is a strong match: - 7 years of fullstack development, primarily with TypeScript and Node.js, - built a React frontend at Reelay for an AI voice assistant analyzing customer calls, - the product processed audio through transcription, chunking, embeddings, Weaviate retrieval, and LLM analysis to generate summaries, agreements, action items, and key questions, - developed the frontend against GraphQL APIs while also working on retrieval logic, structured LLM outputs, hallucination reduction, and latency/cost optimization, - designed high-load, real-time systems using WebSockets, Centrifugo, RabbitMQ, Redis, PostgreSQL, and ClickHouse, - comfortable taking ownership: previously led three developers…

Ask HN: Who wants to be hired? (August 2026)

Location: La Center, WA, USA Remote: Yes Willing to relocate: Yes Technologies: Python, FastAPI, Node.js, React, Next.js, TypeScript, LangChain, LangGraph, LlamaIndex, OpenAI, Claude, Gemini, RAG, Agentic AI, Vector Databases (Pinecone, Weaviate, FAISS, pgvector), AWS (Bedrock, SageMaker, ECS, Lambda, EC2, S3), GCP, Docker, Kubernetes, PostgreSQL, Redis, Elasticsearch, Kafka, WebSockets, LiveKit, Deepgram, Whisper, ElevenLabs Résumé/CV: https://drive.google.com/file/d/16OnzHA6ljIFV0jh4TCLdAMgB5__... Email: benjaminkrueger1@outlook.com Summary: Senior AI Engineer with 9+ years of software engineering experience, including 5+ years building production AI applications. I've developed multimodal AI systems, RAG platforms, AI agents, real-time voice assistants, an…

Ask HN: Who wants to be hired? (August 2026)

Location: North Fort Myers, FL, USA Remote: Yes Willing to relocate: Yes Technologies: Python, FastAPI, Java, Spring Boot, React, Next.js, TypeScript, Node.js, LangChain, LangGraph, OpenAI, RAG, AI Agents, LLMs, Vector Databases (pgvector, Pinecone, Weaviate), Semantic Search, Whisper, Deepgram, LiveKit, AWS (Bedrock, SageMaker, Lambda), Azure OpenAI, GCP Vertex AI, PostgreSQL, MongoDB, Docker, CI/CD Résumé/CV: https://drive.google.com/file/d/1f0aYmJxWozrWeXMf8ST6QDM-038... Email: jzachariah940@gmail.com Summary: Senior AI Full-Stack Engineer with 8+ years of experience building production-grade AI applications, LLM-powered products, and cloud-native platforms. I specialize in Generative AI, RAG systems, AI agents, conversational AI, and real-time voice …

Show HN: Low-latency local LLM runner via OpenJDK Panama FFM (Java 22)

I addressed this a little bit in the comment below, but the cycles add up. I'm doing some pretty crazy things higher up in the stack, that I'm not quite ready to release yet. But even micro optimizations here add up at the scale I'm working at to allow me the headroom I need. I'm relying on a high-frequency recursive agentic loop that chokes a real-time guarantee without every optimization I can give it. I started by removing the IPC overhead from a weaviate db connection, and doing all my vector math in house with a lightweight sqlite db. This became the next obvious target for optimization once I saw how much that saved me doing things in-house.

Ask HN: Who wants to be hired? (July 2026)

Location: Austin, TX Remote: Yes Willing to relocate: No Technologies: • Programming languages: Go, Python (FastAPI, Flask), Node.js, Java (Spring Boot), PHP. • Backend architecture: microservices, REST APIs, event-driven design, idempotency, concurrency. • Cloud and DevOps: Amazon Web Services (AWS) S3, Lambda, EC2; Kubernetes; Docker; CI/CD pipelines. • Data stores: PostgreSQL, MySQL, Redis, Memcached. • Messaging: Apache Kafka, RabbitMQ, Google Pub/Sub. • AI and machine learning: retrieval-augmented generation (RAG), vector databases (Pinecone, Weaviate), large language model (LLM) APIs. • Observability: Prometheus, Grafana, Datadog, Elasticsearch Logstash Kibana (ELK), distributed tracing. • APIs and security: gRPC, GraphQL, OAuth 2, JSON Web Tokens (JWT), role-based access …