Principal AI Platform Engineer

UL Solutions•Austin, TX

6d•Hybrid

About The Position

The Principal AI Platform Engineer is a technical leader responsible for defining and driving the architecture, strategy, and execution of AI platform capabilities across the ULTRUS platform and broader UL Solutions product portfolio. This role owns the design and evolution of core AI platform services, including scalable RAG (Retrieval-Augmented Generation) pipelines, advanced multi-agent orchestration frameworks, and enterprise-grade APIs and microservices. Operating with significant autonomy, this individual ensures the platform meets the highest standards of scalability, reliability, security, and cost-efficiency, while enabling rapid adoption of AI across products. They guide cross-team engineering efforts, establish best practices for agentic AI systems and LLM integration, and influence long-term platform direction. In addition to hands-on architecture and development, the Principal Engineer mentors senior engineers, drives technical excellence, and partners with product and leadership teams to translate business priorities into robust, production-ready AI platform capabilities.

Requirements

10+ years in software engineering with strong distributed systems / SaaS platform experience
4+ years building production AI/ML or LLM-based systems (RAG, APIs, agents, or ML services)
Deep experience with Azure AI ecosystem (Azure OpenAI, AI Foundry, Azure ML, AKS, AI Search)
Strong hands-on expertise in AI frameworks (LangChain, LangGraph, Semantic Kernel, or similar)
Proven ability to design scalable AI platforms, APIs, and microservices architectures
Strong understanding of RAG systems, retrieval optimization, and LLM limitations (hallucination, safety, evaluation)
Experience with Kubernetes, Docker, CI/CD, and production observability practices
Demonstrated technical leadership, mentoring, and cross-team architectural influence
Familiarity with AI governance, responsible AI, and enterprise compliance environments

Responsibilities

Define and drive the AI platform architecture and technical strategy across ULTRUS and broader product portfolio
Design and evolve core AI platform services (RAG, agentic workflows, APIs, orchestration frameworks) for enterprise-scale use
Establish standardized patterns for LLM integration, model routing, and AI service consumption across teams
Lead design of scalable RAG and knowledge retrieval systems, including ingestion, embeddings, and retrieval optimization
Own platform-level decisions on infrastructure (Azure, AKS, vector DBs, CI/CD, observability) for performance, cost, and security
Define and implement AI observability, evaluation, and guardrails (latency, quality, drift, safety, cost)
Provide technical leadership and mentorship across teams; drive architecture reviews and engineering standards
Partner with product and leadership to translate business priorities into reusable AI platform capabilities