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DV Trading

AI Engineer Intern - Summer 2027

ChicagointernshipinternAdded 2 days ago

About this role

Build AI-powered internal tooling for alert response and operational insights at a Chicago-based financial services firm. This DevOps-embedded internship focuses on prototyping generative agents over observability data and internal documentation, with emphasis on safety, traceability, and governance.

What you'll do

  • Design and prototype agentic workflows with tool use, policy boundaries, and human-in-the-loop controls
  • Learn observability stack (Prometheus, Grafana, Loki, Tempo, Alertmanager) and build a generative agent for alert mitigation suggestions
  • Build and iterate RAG systems over permissioned internal data (runbooks, tickets, docs, postmortems) with proper citation
  • Collaborate with platform teams to safely expose observability and operational context to agents
  • Outline design for agentic remediation with guardrails; implement only approved, reviewed changes
  • Document experiments, limitations, evaluation approach, and safety assumptions; manage changes via Git

What they're looking for

  • Generative AI / LLM fundamentals
  • Retrieval-Augmented Generation (RAG)
  • Python or similar systems language
  • Observability tools (Prometheus, Grafana, Loki, Tempo, Alertmanager)
  • Git and version control workflows
  • API design and integration
  • Security and access control principles
  • Agent/agentic systems design
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DV Trading

DV Trading is a proprietary trading firm that develops high-performance, low-latency algorithmic trading platforms and systems. They are hiring software developers to build and optimize trading technology, as well as trade support engineers to monitor platforms, manage infrastructure, and support traders across their operations.

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Likely interview questions

  • How would you design a generative agent that provides safe, traceable mitigation steps for observability alerts?
  • Walk us through how you'd build a RAG system over internal runbooks and postmortems—what challenges would you anticipate with permissioning and citation?
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