Associate AI Engineer
On-siteColumbus, Ohio, United States
Columbus, Ohio, United StatesOn-siteFull TimeEntry LevelMasters DegreeSmall
Full TimeEntry LevelMasters DegreeSmall
Job Summary
Own AI projects end to end, from problem scoping and prompt engineering to integration, testing, deployment, and documentation. Build and deploy agentic workflows and LLM-powered tools that solve real operational problems, designing multi-agent systems with clear handoffs and built-in checks. Work directly with stakeholders to turn vague problems into clear requirements, then run proofs of concept to pressure test ideas before taking them into production. Monitor, debug, and improve existing systems, while applying security and governance practices including risk tiering and guardrails to everything you build.
Required Qualifications
- Bachelor's or master's degree in Computer Science, Information Systems, AI/ML, or a related technical field, or equivalent practical experience
- Demonstrated experience building with LLMs or agentic workflows, such as a capstone project, hackathon project, internship deliverable, or personal project
- Enthusiasm for AI technologies demonstrated through academic projects, hackathons, etc.
- Proficiency in Python and the ability to read and debug code written by others
- You want to understand how LLMs and agentic systems actually work, not just how to use them
- An instinct for security and responsible AI practice; you think about what could go wrong before it does
- Strong written communication
- Ability to take ownership of a project and drive it to completion
Desired Qualifications
- Experience with agentic frameworks such as LangChain, LangGraph, or CrewAI
- Exposure to evaluation frameworks or techniques for testing AI system performance
- Familiarity with tracing or observability tools used to debug multi-step agent behavior
- Experience with API integration work or connecting agents to external tools and data
- Prior exposure to AI security, red teaming, or governance practices
- Familiarity with cloud platforms such as AWS, GCP, or Azure
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