Quick overview
Job description
***This role is 3 days onsite each week in Chicago, hybrid remote***
***We are unable to provide sponsorship for this permanent full-time role in Chicago***
***Position is bonus eligible***
Prestigious Financial Institution is currently seeking an Artificial Intelligence Engineer with strong LLM experience Candidate will be responsible for the design and delivery of agentic AI systems end-to-end, from architecture through production deployment.
Responsibilities:
- Architect agent orchestration patterns, tool and context integration, and evaluation pipelines for reliability in a regulated environment
- AI infrastructure supporting agents and applications on AWS, and contribute 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 function
- 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
Qualifications:
- Experience mentoring or elevating the work of junior engineers
- Demonstrated ownership of production systems from design through deployment
- Ability to work effectively in a still-forming, fast-moving team environment
- This position is not eligible for employment be legally authorized to work in the United States without the need for sponsorship now or in the future.
- Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's preferred
- 4-7 years of software engineering experience, with production AI/LLM systems experience preferred
Technical Skills:
- Required: Strong Python; proficient SQL; solid distributed systems and API design fundamentals
- Required: Hands-on experience building LLM-powered applications or agentic systems
- Required: Working knowledge of AI-specific risk areas (prompt injection, output validation, hallucination mitigation, data privacy), or demonstrated ability to build this expertise quickly
- Required: Cloud infrastructure experience (AWS preferred); comfort with Docker, CI/CD, and containerization fundamentals
- Preferred: Direct experience with Claude, the Anthropic API, or Claude.ai/Console
- Preferred: Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations
- Preferred: Production experience operating LLM-powered applications or agentic systems at scale
- Preferred: Kubernetes and infrastructure-as-code (Terraform)
- Preferred: Background in financial services, derivatives, or other regulated industries
- Preferred: Exposure to AI security practices such as red-teaming or adversarial testing of model inputs and outputs
- Preferred: Data engineering experience (pipelines, data modeling), particularly for candidates interested in AI infrastructure work
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