Principal Artificial Intelligence Engineer

Chicago 13 days agoFull-time External
1.4m - 1.6m / yr
• **Hybrid, 3 days onsite, 2 days remote*** • **We are unable to sponsor as this is a permanent full-time role*** Responsibilities: • Partner with the Executive Director, AI Engineering to help define and execute on the company AI technical roadmap • Lead and partner on the architecture of scalable systems incorporating LLMs and AI into organizational processes and infrastructure • Provide technical mentorship to junior engineers on engineering best practices and system design • Conduct code/architectural reviews ensuring production readiness, safety, and adherence to high security and compliance standards • Implement testing, evaluation, and monitoring frameworks for AI systems including hallucination detection and bias assessment • Establish safety guardrails and responsible AI practices for LLM applications in a regulated environment • Connect AI agents to organizational systems and workflows • Foster continuous learning culture in a rapidly evolving AI landscape Qualifications: • Bachelor's or Master's in Computer Science or related technical field • 10+ years software engineering/systems architecture experience with strong technical leadership • 5+ years as senior technical contributor on complex production systems • Expert in Python and proficient in SQL • System design expertise: monolithic and microservice architectures, distributed systems, event-driven architectures, APIs • Hands-on experience in data (e.g., data engineering, data pipelines, data transformation) • Foundational experience with LLMs and familiarity with multiple frontier lab models (e.g., Gemini, Claude, GPT) • Familiarity of risk vectors in AI applications including hallucinations, bias, prompt injection, data privacy • Production experience with AI applications or LLM-powered systems • Experience with RAG architectures and context engineering • Familiarity with diverse LLM provider APIs and experience connecting agents to systems • Experience tinkering with frontier lab tools and products • Cloud platforms/technologies: AWS, Docker, Kubernetes, CI/CD, Terraform