Bachelor’s Degree or higher in a quantitative field (Statistics, Computer Science, Engineering, Mathematics)
5-7+ years of experience in AI/ML engineering, applied machine learning, natural language processing, and/or AI systems development
2+ years of hands-on experience building production LLM or AI agent systems
Demonstrated experience building agents used in production by external customers or enterprise/business users with hands-on experience using LangGraph, LangChain, or related agent orchestration frameworks
Experience building systems that turn messy, unstructured source material into validated structured output using schemas, ontologies, or data contracts with entity resolution, disambiguation, and conflict resolution
Strong Python engineering skills and experience building scalable production software systems
Experience designing agent architectures involving tool use, reasoning flows, retrieval, memory, guardrails, and workflow orchestration
Experience developing AI evaluation systems, including LLM-as-judge, guardrail evaluation, regression testing, and production quality measurement
Strong understanding of RAG, embeddings, retrieval quality, and knowledge-grounded generation
Experience deploying or operating systems in AWS cloud environments
Daily use of AI coding tools such as Codex, Claude Code, Cursor, or similar tools as part of software development workflows
Strong engineering judgment, ability to work independently, and comfort operating as a senior individual contributor on ambiguous technical problems
Master’s Degree or higher in a quantitative field (Statistics, Computer Science, Engineering, Mathematics)
Experience building or using knowledge graphs for enterprise knowledge modeling, retrieval, reasoning, or personalization
Experience with enterprise automation platforms, customer experience systems, workflow automation, or AI-powered business process automation
Familiarity with security, compliance, auditability, and governance requirements for enterprise AI systems