We’re building real, production-grade AI agents—not just demos. If you’re hands-on, curious, and love exploring new agentic patterns, you’ll feel at home here.

• Design, build, and ship long‑running/background agents that can recover from failures, resume work, and keep state.
• Implement tool-using agents (function calling / tools API) that operate across internal services and third‑party systems.
• Make agents data‑heavy: stream, batch, and chunk large inputs; orchestrate multi‑step jobs; manage memory; persist context.
• Build evaluation + observability for agents: traces, metrics, playbooks, test harnesses, offline/online evals, A/Bs.
• Prototype fast: compare models, prompts, and planning strategies; run experiments; instrument everything.
• Collaborate with product + customers to turn messy workflows into robust agent workflows.

• Shipped at least one serious agent project (not a weekend toy). Bonus: it ran continuously, touched real data, or automated a real business process.
• Python as your main language (TypeScript a plus). Comfortable with async, APIs, and writing clean services.
• Experience with agent frameworks (e.g., LangGraph, OpenAI Agents sdk, CrewAI, Tools, custom planners) — or you’ve built your own light framework.
• Worked with RAG / vector search (pgvector, Pinecone, Weaviate, FAISS) and structured outputs(Pydantic/JSON Schema).
• Familiar with queues + schedulers (Celery, RQ, Kafka, Airflow/Prefect) and background job design.
• Practical infra: containers, CI, cloud (GCP/Azure), secrets, monitoring.

• Multi‑agent patterns, graph planners, tool routing, function‑calling best practices.
• Retrieval over large, messy corpora; compound systems that mix search, extraction, and decision‑making.

• Small team, big ownership. Ship iteratively, measure, and improve.
• Pragmatic about models and vendors; choose what works and prove it with evals.
• We care about reliability, safety, and user trust as much as speed.

Send us the GitHub link to the best agent project you’ve worked on and add:

1. What problem it solves and why you built it.
2. One design decision you’re proud of.
3. One thing you’d improve if you had another week.