We're hiring for two important roles at @ai_atoms , our newest bet at @saas_labs. We help mid-market and enterprise teams with deploying AI solutions, powered by our own proprietary AI operations platform. Open Roles: Applied AI Consultant - sits across the table from a CFO or VP of Ops and walks out with a scoped problem, a credible architecture, and a path to measurable value. Then stays accountable until that value is real. It's a mix of Solution Engineer Solution Selling role. Applied AI Engineer - takes that scoped problem and ships a production-grade AI system end-to-end. RAG, agents, evals, the works. Then keeps it alive when real users and real edge cases show up. If you love playing around with HF datasets, trying new models, have built some crazy setup using OpenClaw - you're going to absolutely love this. AtomsAI sits inside SaaS Labs, the team behind @justcallhq , @callpage_io and @serviceagentai. 6,000 customers globally. Over a billion conversations powered. Raised over $55mil in venture capital, doing tens of millions in real ARR & profitable. Now we're building the team that pushes it further. 5 days in office (preferrably Noida or Bangalore). High ownership. High Intensity. Fast cycles. No Large Team Office BS like bureaucracy or politics. Just high value problem solving work. If you've been waiting to build AI that actually works in production - not decks, not demos - let's talk. Roles in the comments. Tag someone who'd be a fit. 👇

I just open-sourced ContextDB - a unified context layer for AI agents. It replaces the patchwork of Pinecone Redis Postgres glue code that every agent team builds with one system that actually understands memory. 82 tests passing. <5ms search latency. Apache 2.0. Thread on why this matters:

Benchmarks (v0.1.0, SQLite backend, no FAISS): Write: 1930/sec Search p50: 3.4ms Search p95: 4.3ms (target was <100ms) PII detection: 111K texts/sec Vector self-retrieval: correct All 82 tests passing Full benchmark report in the repo.