10+ years of software engineering experience, including 3+ years in AI/ML or AI application development
Strong proficiency in Python and API development (REST, GraphQL, webhooks)
Hands-on experience with enterprise integration platforms (e.g., Workato, MuleSoft, Zapier)
Experience working with LLM APIs (OpenAI, Anthropic, Google Gemini, or similar)
Deep understanding of agentic architectures, RAG patterns, and prompt engineering
Experience designing scalable, distributed systems in cloud environments (AWS, GCP, or Azure)
Strong knowledge of microservices, event-driven architecture, and integration design patterns
Experience with CI/CD, infrastructure as code, and DevOps practices
Understanding of data security, privacy, and compliance considerations (SOC 2, GDPR)
Experience deploying agentic AI systems in production environments
Familiarity with iPaaS platforms (Workato preferred) and enterprise automation ecosystems
Experience with Google Workspace or Microsoft 365 automation and extensibility
Knowledge of Model Context Protocol (MCP) or similar interoperability standards
Experience implementing AI governance frameworks in enterprise settings
Background in infrastructure, energy, or high-performance computing environments
Contributions to open-source AI projects or technical thought leadership