AI Engineer Intern (AI)

Location: Chicago, United States

Compensation: $40.00–$50.00 per hour

Company

hirify.global is a proprietary financial trading firm using its own capital, trading strategies, and risk management methodologies across worldwide financial markets.

What you will do

• Prototype a generative assistant that analyzes approved observability sources and proposes structured alert-mitigation suggestions.
• Build and iterate on retrieval-augmented generation over permissioned runbooks, tickets, documentation, system designs, and postmortems.
• Design agent workflows with tool use, policy boundaries, human approval, and traceability to source queries and signals.
• Explore scoped implementations for agentic remediation without autonomous production changes.
• Collaborate with platform and service teams to expose operational context safely to internal agents.
• Document experiments, limitations, evaluation methods, and safety assumptions, and ship changes through Git.

Requirements

• Pursuing a BS or MS in Computer Science, Computer Engineering, Information Systems, or a related field.
• Expected graduation by Summer 2028.
• Hands-on experience using AI tools such as LLM APIs, assistants, or coding agents; experience building agents is preferred.
• Experience with RAG, including retrieval design, chunking, evaluation, grounding, or production-minded prototyping.
• Proficiency in Python for prototyping and integration, with experience consuming and creating APIs and working with JSON and YAML.
• Experience with Git workflows and strong judgment around sensitive data, secrets, logging, and internal policies.

Nice to have

• Linux fundamentals, including shell usage, processes, logs, permissions, and troubleshooting.
• Networking fundamentals covering DNS, TCP/HTTP/S, ports, load balancing, and Ingress.
• Kubernetes fundamentals, including debugging pods, services, and ingress.
• Coursework or projects involving Kubernetes, Prometheus, Grafana, OpenTelemetry, CI/CD, Terraform, Ansible, AWS, GCP, or Azure.

Culture & Benefits

• Project-focused internship embedded within the DevOps team.
• Work centers on internal, production-adjacent tooling rather than customer-facing ML models.
• Permissioning, auditing, logging, and cost controls are required throughout the work.
• Agentic remediation is limited to approved implementations under platform review, with no autonomous production changes.