Senior Artificial Intelligence Engineer

Salary: $140k-$160k + 15% bonus

Location:

Chicago, IL

Hybrid: 3 days onsite, 2 days remote

* We are unable to provide sponsorship for this role*

The AI Research & Engineering (AIRE) team is building the company's first generation of agentic AI capabilities on Anthropic's Claude models and AWS infrastructure. The Senior AI Engineer owns the design and delivery of agentic AI systems end-to-end, mentors junior engineers, and contributes technical judgement on AI application and/or AI infrastructure work in a largely greenfield environment.

• Bachelor’s degree in Computer Science, Engineering, or related
• 4-7 years of software engineering experience, with production AI/LLM systems experience preferred
• Strong Python; proficient SQL; solid distributed systems and API design fundamentals
• Hands‑on experience building LLM‑powered applications or agentic systems
• Working knowledge of AI‑specific risk areas (prompt injection, output validation, hallucination mitigation, data privacy), or demonstrated ability to build this expertise quickly
• Cloud infrastructure experience (AWS preferred); comfort with Docker, CI/CD, and containerization fundamentals
• Experience mentoring or elevating the work of junior engineers

• Direct experience with Claude, the Anthropic API, or Claude.ai/Console
• Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations
• Production experience operating LLM‑powered applications or agentic systems at scale
• Kubernetes and infrastructure-as-code (Terraform)
• Background in financial services, derivatives, or other regulated industries
• Exposure to AI security practices such as red‑team­ing or adversarial testing of model inputs and outputs
• Data engineering experience (pipelines, data modeling), particularly for candidates interested in AI infrastructure work

• Own the design and delivery of agentic AI systems end-to-end, from architecture through production deployment
• Architect agent orchestration patterns, tool and context integration, and evaluation pipelines for reliability in a regulated environment
• Own AI infrastructure supporting AIRE's agents and applications on AWS, and contributes to the team's growing infrastructure self-sufficiency
• Implement technical safeguards against AI‑specific risks, including hallucination detection, prompt injection defense, and output validation, in collaboration with AI Governance
• Build audit logging and human-in-the-loop checkpoints into agentic workflows so agent actions remain traceable and reviewable in a regulated environment
• Mentor Associate and Senior Associate engineers through code and architecture review
• Contribute technical point of view to the team's evolving engineering standards and practices, in partnership with the Executive Director