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