Position: 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
