Bachelor's degree in computer science, engineering, or a related field; Master's degree preferred
10+ years of experience in software engineering or platform architecture, including 3+ years in technical leadership or people management roles leading cross-functional engineering teams
Proven track record building and scaling GenAI products in production, with ownership of architecture, delivery, post-launch iteration, reliability, and performance
Experience leading teams across data engineering, data science, and full-stack development, with the ability to set technical direction, mentor senior ICs, and drive accountability across workstreams
Strong expertise in GenAI systems, including LLMs, prompt engineering, tool calling, RAG pipelines, NL2SQL, vector databases, embeddings, and multi-agent orchestration frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel
Proficiency with AI-assisted software development methodologies and tools, including Cursor, Claude Code, and comparable agentic coding environments; comfortable driving an AI-native SDLC across teams
Strong cloud engineering experience, preferably on AWS, with working knowledge of Kubernetes, CI/CD pipelines, distributed or event-driven systems, message queues, and real-time data flows
Hands-on experience with Snowflake data modeling, multi-tenant data isolation, and ETL/ELT pipelines for enterprise-scale data onboarding
Familiarity with modern full-stack development, including TypeScript/Node.js, NestJS, React/Next.js, Python/FastAPI, and monorepo tooling such as Nx and pnpm
Knowledge of AI governance, security, compliance, and observability, including guardrails for safety and reliability, prompt tracing, cost tracking, and failure analysis
Strong communication and stakeholder management skills, with the ability to align product leaders, partners, delivery teams, and cross-functional stakeholders around technical and business priorities