Overview
Hybrid
Depends on Experience
Full Time
Skills
AI
artificial intelligence
engineer
data
LLM
large language
model
aws
docker
kubernetes
terraform
IaC
Job Details
Technical Lead Engineer, Artificial Intelligence
Salary: Open + Bonus
Location: Chicago, IL
Hybrid: 3 days onsite 2 days remote
*We are unable to provide sponsorship for this role*
Qualifications
- Bachelor's or Master's degree 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 architecture, distributed systems, event-driven architecture, APIs
- Hands-on experience in data (e.g., data engineering, data pipelines, data transformation)
- 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
- Cloud platforms/technologies: AWS, Docker, Kubernetes, CI/CD, Terraform
- Experience with RAG architecture and context engineering
- Familiarity with diverse LLM provider APIs and experience connecting agents to systems
Responsibilities
- Partner with the Executive Director, AI Engineering to help define and execute on AI technical roadmap
- 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
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