You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code
You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute
You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks
You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency
You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs
You have experience owning the full scope of a use case end-to-end
You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting
Experience setting architectural standards for AI and agentic systems across distributed teams
Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it
Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms)
Experience with enterprise security, compliance, or auditability requirements for AI systems