About the role Join Optibus' GenAI team to build and extend the AI assistant embedded across our product suite. The platform is a production LLM agent system that's integrated into multiple host applications, backed by a RAG knowledge base and an evaluation-driven development workflow. You'll work end-to-end: agent design, tool implementation, retrieval quality, integration into existing product UIs, cloud infrastructure, and evaluation/observability. The platform already ships to customers — you'll extend it, raise its quality bar, and help define where it goes next. What you'll do Design and evolve agents - build LLM agents with tool use, routing, and human-in-the-loop flows. Implement tools and integrations - expose product capabilities to the agent, with multi-tenant context, via internal APIs and MCP servers. Own retrieval quality - contribute to our RAG pipeline end-to-end: ingestion, embeddings, vector search, and reranking. Define and evolve host integration contracts - collaborate with host application teams to integrate the assistant into product UIs built on different frontend stacks. You own the shared remote module and the integration API; host teams own their stacks. Drive evaluation-led development - write evaluators (rule-based, LLM-as-judge, multi-turn), maintain CI eval gates, and use traces and feedback to debug production behavior. Operate the platform - own deployments, observability, and the performance and cost of LLM-backed services. Establish engineering practices** for AI-specific work: prompt versioning, eval coverage, testing, and code review. Requirements 5+ years of professional software engineering experience. Strong TypeScript — the primary language across our backend, frontend, and agent code. Production experience with LLM-based applications, including prompt engineering, agent/tool-calling design, and RAG. Hands-on experience with an agent framework (e.g., LangGraph, LangChain). Vector databases and semantic search
