Principal Artificial Intelligence Engineer (LLM) (Chicago)

NO SPONSORSHIP - NO OPT

PRINCIPAL ARTIFICIAL INTELLGIENCE ENGINEER

SALARY : $200K - $220K PLUS 30% BONUS

LOCATION : CHICAGO

HYBRID 3 DAYS ONSITE

SELLING POINTS : AI Research and engineering team. You will need strong software engineering and tech leadership. You will help define and execute AI technical roadmap, incorporate LLM and AI into processes and infrastructure. Large language models (LLMs) 10 years software engineering system architecture. Expertise python proficient in SQL system design expertise monolithic and microservices architecture distributed systems event driven architecture data engineering data pipelines data transformation AWS Docker Kubernetes CICD infrastructure as a code terraform

Lead and partner on the architecture of scalable systems incorporating LLMs and AI into organizational processes and infrastructure

Design and build production applications in support of organizational use cases

Provide technical mentorship to junior engineers on engineering best practices and system design (no direct reports)

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

Evaluate emerging technologies and recommend adoption strategies

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

Experience mentoring and reviewing the work of junior engineers

Exceptional communication skills explaining complex technical concepts

Strong interest in AI / LLM space with demonstrated commitment to continuous learning

Preferred

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

Infrastructure as code : Terraform

Experience in financial market infrastructure or derivatives industry

Background in regulated environments