5+ years of professional software engineering experience with demonstrated progression into technical leadership
Deep proficiency in Python with experience architecting production backend systems (Django strongly preferred)
Strong frontend development skills with React and TypeScript, including experience with complex state management
Significant hands-on experience with LLM APIs and building orchestration systems (agent workflows, tool calling, multi-step reasoning)
Experience designing and implementing MCP integrations, including tool servers, embedding models, and context management strategies
Track record of defining technical roadmaps and leading projects from conception through delivery
Experience mentoring engineers and elevating team technical practices
Strong ability to make decisions under ambiguity and communicate technical trade-offs to stakeholders
Demonstrated curiosity and continuous learning in the rapidly evolving AI/LLM space
Experience building internal developer platforms, SDKs, or shared AI/ML infrastructure
Familiarity with LLM orchestration frameworks (LangChain, LangGraph, or equivalent)
Deep expertise in agent architectures: multi-agent systems, tool use, planning algorithms, or memory systems
Experience with prompt optimization, evaluation frameworks, or LLM observability tools (LangSmith, Weights & Biases)
Background in building AI features that shipped to enterprise customers
Experience at a B2B SaaS company scaling from Series B through growth stage
Familiarity with sales performance, commissions, or financial software domains
Contributions to AI/ML open-source projects or technical publications