About Us Mindprint is the latest product from Particle Execution , a company building custom AI automations and agents for fast-scaling businesses. We're on a mission to bring judgment and memory to AI. We’re currently rolling out a suite of AI Agents capable of handling real tasks like writing platform-native content, syncing with CRMs, and managing client briefs. Underneath it all is a powerful memory system that learns from your feedback and context - making agents smarter over time. We’ve just launched to our first paying customers and are scaling fast. The Role We’re looking for a senior backend engineer who can build the next layer of our agent infrastructure - specifically: Architecting and scaling agent workflows (LangGraph or LangChain-style) Architecting and scaling our products backend Designing APIs that support dynamic, memory-augmented agents Integrating with 3rd-party tools like CRMs, Slack, Notion, Google Drive Helping productionize memory (vector DBs + custom feedback logic) You’ll work closely with our Software Development team, Product Designer, AI automation engineers, and product founders - shipping fast, learning from users, and iterating quickly. What You’ll Work On Building dynamic agent routing workflows (LangGraph-style graphs) Developing & maintaining backend APIs (FastAPI or similar) Integrating external systems like Hubspot, Google Drive, Notion, etc. Handling vector-based memory + feedback and storing context intelligently Contributing to overall product architecture (auth, user access, security, etc.) Potentially helping architect early self-serve features (e.g. Zapier-style connections) Requirements 4+ years backend development experience in Python Experience with Postgres as well or any SQL based database Strong expertise in in AI & ML & NLP Strong knowledge of FastAPI , Flask, Django or similar Experience with LLM tooling : LangChain, OpenAI, Pinecone/Weaviate/Chroma, etc. Comfortable designing and implementing stateful workflows Solid understanding of async Python and API-first development Familiarity with vector databases, embeddings, and RAG concepts Hands-on experience building and maintaining scalable systems Startup-ready: fast-moving, self-directed, hands-on Bonus (but not required) Experience using or contributing to LangGraph Background in agent-based modeling or state machines Experience building agent orchestration or workflow engines Familiarity with CrewAI, AutoGen, or similar frameworks DevOps skills (Docker, CI/CD, GCP, etc.) Why Join Us Be part of a zero-to-one product with massive potential Work directly with experienced founders and a sharp technical team Influence architecture and product strategy from day one Get exposure to cutting-edge AI infrastructure