Principal AI Engineer, Enterprise Generative AI

What you'll do

• Design and own enterprise-grade GenAI architectures including RAG pipelines, agentic workflows, and multi-model routing.
• Drive production readiness by ensuring scalability, resilience, observability, and cost efficiency for AI solutions.
• Lead architectural decisions for data ingestion, vector databases, model selection, and latency optimization.
• Partner with business teams to translate requirements into technical designs and deliver high-impact GenAI use cases.
• Establish reference architectures and reusable patterns to accelerate GenAI adoption across different lines of business.
• Ensure all AI solutions comply with risk, cyber, and model governance standards including data protection and guardrails.
• Mentor senior and staff-level engineers to raise the technical bar across the enterprise.
• Influence the central AI platform roadmap by providing feedback from real-world production use cases.

What we're looking for

• 7+ years of software engineering experience with significant depth in AI/ML or data-intensive systems.
• 2+ years of experience in Python programming language.
• 2+ years of experience designing and delivering production-scale Generative AI systems in an enterprise environment.
• 2+ years of experience in LLMs, prompt engineering, and RAG architecture.
• 2+ years of experience in vector databases, semantic search, and API-driven, cloud-native architectures.
• 2+ years of experience in distributed systems and performance optimization.
• Strong understanding of non-functional requirements including security, scalability, resiliency, observability, and cost management (preferred).
• Experience operating in highly regulated environments (financial services strongly preferred).