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