Lead AI Engineer

Title Resources Guaranty

3h•Remote

About The Position

We’re hiring a product-minded AI Engineering Lead to build and scale production AI agents that eliminate manual work across TRG. You’ll lead end-to-end problem ownership—from workflow discovery and system design to deployment, adoption, and continuous optimization—ensuring solutions are fast, reliable, and deliver measurable business impact. This role requires a hands-on technical leader who can both architect and build, while partnering closely with internal stakeholders to translate complex business processes into practical, production-ready AI solutions. You’ll set the standard for how we design, deploy, and scale AI across the organization. This is a builder-led leadership role—focused on delivering real, production-grade agents used by internal teams, not research or prototypes.

Requirements

3–8 years building and shipping software to production (AI experience can be newer if engineering fundamentals are strong)
Strong coding ability in C# and modern TypeScript/React; consistently produces maintainable code, tests, and high-quality PRs
Hands-on experience deploying LLM/agent solutions using Azure AI Foundry (or adjacent Azure AI services) and operating them in production
Proven ability to lead and mentor a small, high-performing team, setting technical direction while remaining hands-on in delivery
Comfort with ambiguity—able to translate loosely defined problems into clear specs, milestones, and working systems
High ownership and bias to action—focuses on shipping, measuring impact, and iterating quickly over polishing demos
Strong communication skills, with the ability to engage effectively with both technical and non-technical stakeholders

Nice To Haves

Experience with RAG over internal documents (chunking, indexing, retrieval tuning) and evaluation of retrieval quality
Experience integrating agents with internal systems via APIs, queues, and workflow tools
Familiarity with security-focused or regulated environments (PII handling, least-privilege access, auditability)
Experience setting up automated evals (golden sets, regression tests) for prompts/agents

Responsibilities

Own AI agent projects from zero to one: problem framing, design, implementation, deployment, monitoring, and iteration
Embed with business teams to map workflows (title production, underwriting, ops), identify high-leverage bottlenecks, and streamline them using AI
Design agent architectures (tools/functions, memory/state, retrieval, guardrails) and write prompts that are testable and versioned
Build full-stack features in C# and TypeScript/React that make agents usable, safe, and fast for internal users
Ship on Azure using Microsoft/Azure AI Foundry: model selection, evaluation, deployment pipelines, and production operations
Instrument quality: define success metrics, create evals/test suites, reduce hallucinations and failure modes, and drive reliability over time
Partner with security/compliance to ensure data handling and access patterns are appropriate for enterprise workflows