Principal AI Engineer

We are looking for an experienced Principal AI Engineer to lead the architecture, technical strategy, and evolution of enterprise-scale AI platforms and GenAI-powered solutions. The role requires strong hands-on experience with production AI systems, RAG, AI orchestration, distributed platforms, and AI engineering standards. Responsibilities Define and own the architecture of enterprise-scale AI platforms Design and develop production-grade GenAI systems and AI-powered solutions Lead the development of RAG pipelines, retrieval infrastructure, and AI orchestration frameworks Design scalable distributed systems, APIs, data pipelines, and event-driven architectures Establish standards for AI quality, evaluation, observability, governance, and model lifecycle management Define and scale AI-driven software-development practices, including tools, guardrails, and automation patterns Drive architecture decisions and technical alignment across multiple engineering teams Build reusable AI platform components, frameworks, and internal tooling Conduct architecture and code reviews and mentor senior and Staff-level engineers Collaborate with product, data, security, infrastructure, and engineering teams Document architectural decisions, technical standards, and organizational best practices Lead technical initiatives across distributed international teams Requirements 12+ years of professional software-engineering experience Significant experience working at Staff or Principal Engineer level Strong hands-on experience building and deploying production-grade GenAI / LLM systems Expert-level Python engineering skills Strong experience with LLM applications, RAG, vector databases, and retrieval infrastructure Experience with LangChain, LlamaIndex, semantic search, or similar AI frameworks Strong understanding of AI evaluation, model lifecycle management, observability, and MLOps Proven experience designing and evolving large-scale distributed systems Strong knowledge of APIs, data pipelines, event-driven systems, and high-scale platforms Experience driving architecture and platform initiatives across multiple teams Hands-on experience with AI-assisted development tools such as Copilot, Claude Code, or Cursor Strong engineering fundamentals in code quality, testing, CI/CD, and observability Ability to influence technical decisions and drive alignment without formal authority Experience collaborating with distributed teams across different regions and time zones Professional English, Upper-Intermediate or higher Nice to have Experience building enterprise AI platforms or internal AI developer platforms Experience with Kubernetes, cloud platforms, and infrastructure automation Experience with MLOps platforms and model monitoring Experience with event-driven architectures and large-scale data processing Experience establishing AI governance and engineering standards across organizations Experience working with distributed teams across the US, China, and LATAM Experience in enterprise SaaS, FinTech, healthcare, or other complex domains