The board
- Where
- Chicago
- Posted
- Sep 9
Founded 20 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people operating throughout North America, Europe and Asia. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users. Now, DV group affiliates include two broker dealers, a cryptocurrency market making firm, and a bourgeoning investment adviser.
Role Overview:
This is a project-focused internship for an AI engineer embedded on the DevOps team. You will report to the DevOps lead and partner with internal technology teams.
What you'd do
- Design and prototype agent workflows with tool use, policy boundaries, and human-in-the-loop where appropriate.
- Collaborate with platform and service teams to make more observability and operational context available in a safe, governed way for agents.
- Document experiments, limitations, evaluation approach, and safety assumptions; ship changes via Git (branches, merge requests, meaningful commits).
What they want
- Pursuing a BS or MS in Computer Science, Computer Engineering, Information Systems, or a related field
- Expected to graduate by Summer 2028
- Hands-on experience using AI tools (e.g. LLM APIs, assistants, or coding agents) in real projects; preferably experience building an agent (tools, orchestration, or similar—not only prompt-only chat).
- Experience with RAG (retrieval design, chunking, evaluation, grounding, or production-minded prototyping)—including applying it to real or simulated internal/knowledge-base style data, not only public tutorials.
- Python for prototyping and integration; comfortable consuming and creating APIs and working with JSON; able to understand YAML for configs.
- Git workflow: branches, merge requests, meaningful commit messages.
- Strong judgment on data handling: no secrets in prompts/logs, minimize sensitive data, follow internal policies.