Summary
✨ AI‑Generated
A Staff AI Engineer is sought for a hands-on technical leadership role building and deploying production AI systems. You will architect solutions using LLMs, agentic workflows, retrieval-augmented generation and model APIs, make decisions around scalability, reliability, security and cost, mentor engineers, and establish strong practices for AI evaluation and production monitoring.
Highlights
Hands-on technical leadership role combining AI architecture, production engineering, mentorship, and stakeholder collaboration, with a strong focus on scalable and reliable AI systems.
Description
Staff AI Engineer ||MILWAUK EE, WISCONSIN, UNITED STATES w2
Role: Staff AI Engineer (Technical Leadership & Hands-on Development) Location: Hybrid; 2 3 days/week in Milwaukee or Raleigh; Chicago-based candidates considered if able to commute to Milwaukee as needed
Key Responsibilities
Architect, build, and deploy AI systems into production environments Provide technical direction and mentorship to other engineers while remaining hands-on Design solutions using LLMs, agentic workflows, RAG/embeddings, model APIs, and traditional software Make and communicate architectural decisions around technologies, scalability, reliability, security, and cost Partner with stakeholders to understand business problems and shape technical solutions Establish and promote best practices for AI evaluation, monitoring, and production reliability Develop reusable engineering patterns and standards across AI initiatives Lead architecture and raise technical standards across products or domains
Must-Have Qualifications
Demonstrated experience building and deploying AI systems into production (not just POC/integration) Ownership of architecture: technology selection, pattern design, clear communication of tradeoffs Strong hands-on software engineering skills (actively coding and building) Applied experience with LLMs, agents, RAG/embeddings, and modern AI architectures Ability to translate ambiguous business requirements into technical solutions Experience with production-grade AI systems: evaluation, monitoring, reliability, cost, and post-deployment improvement Proven technical leadership and mentorship while remaining involved in development
Preferred/Nice-to-Have Qualifications
Experience building AI products from 0 to 1 Background in startups, high-ownership, or entrepreneurial environments Customer-facing or forward-deployed engineering experience Multimodal AI (voice, image) experience Experience developing reusable AI frameworks or platforms Advanced agentic AI experience Architectural influence across multiple products or teams
Technical Environment
Languages/Technologies: Python, SQL, PostgreSQL, React, C#, iOS, LLMs, agentic AI, RAG/embeddings, cloud development Emphasis on strong engineering fundamentals and AI depth, not specific tech stack experience
Interview Process
Three rounds: two virtual technical interviews (30 minutes each), followed by a possible in-person final round
Additional Notes
Hybrid work model preferred; flexibility for strong candidates Candidates should demonstrate both technical depth and leadership, with strong product/customer focus
