AI Systems Engineer – Agentic AI, Enterprise AI Platforms & Secure AI Workflows

We are looking for exceptional AI systems engineers who enjoy designing and building production AI systems that solve complex enterprise problems. Our work spans agent orchestration, enterprise workflows, knowledge systems, secure AI platforms, human-in-the-loop decision support, and operational intelligence. We value engineers who think in systems, not just software. We're building production AI systems for organizations where reliability, governance, security, and measurable operational performance are essential. We're looking for exceptional engineers who want to help shape how enterprise AI systems are designed, deployed, and governed. Examples of the types of systems we design include: - Multi-agent AI systems - Enterprise AI assistants - Operational workflow automation - AI-powered knowledge systems - Human-in-the-loop decision support - Document intelligence - Retrieval-Augmented Generation (RAG) - AI memory and retrieval systems - AI evaluation and testing frameworks - Secure enterprise AI platforms - AI governance capabilities - Operational intelligence platforms - Technical Experience We Value We're interested in engineers with experience in some combination of: - Python - AI Agent Development - LangGraph - LangChain - Large Language Models - API Development - Vector databases - PostgreSQL - Enterprise system integration - Software architecture - Distributed systems - Secure application design - Experience with OpenAI, Anthropic, MCP, cloud infrastructure, workflow orchestration, observability, or production AI platforms is also valuable. We do not expect expertise in every technology. We care more about engineering judgment than checking every box. We're looking for people who: - Think in systems rather than individual features - Care about production quality - Enjoy solving ambiguous problems - Communicate technical ideas clearly - Balance speed with sound engineering - Build practical solutions rather than chasing hype - Continuously learn and experiment