Summary
✨ AI‑Generated
Join a senior AI engineering function responsible for defining how production agent systems are designed, built, and deployed across a large financial organization. You will establish standards for agent and MCP development, build reference implementations, and help accelerate responsible enterprise-wide AI adoption. The role combines hands-on engineering with architecture, governance, and cross-functional technical influence.
Highlights
Help establish organization-wide standards for production AI and agent systems while building reference implementations that demonstrate scalable engineering patterns. The role offers broad technical impact across a sophisticated financial technology environment and close involvement in AI adoption and governance.
Description
About Us:
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.
Overview:
DV Trading is building a centralized AI function to govern, standardize, and accelerate firm-wide AI adoption.
The Senior AI Engineer defines how the firm builds production agent systems and ships reference implementations that demonstrate the patterns in production.
Job Responsibilities:
Define firm-wide standards for agent and MCP development Build reference agent applications for business teams Design patterns for connecting agents to internal databases, APIs, and knowledge sources Establish security and governance requirements for AI in a regulated trading environment Partner with Security on AI-specific controls (data access, audit, threat detection) Evaluate and adopt infrastructure for agent deployment and observability Partner with stakeholders to identify and deliver high-value use cases
Requirements:
5+ years software engineering; strong Python Production LLM-powered agent systems shipped (not demos) Experience integrating agents with databases, APIs, and internal data sources MCP and/or tool-calling experience in production Security experience in regulated or sensitive-data environments Kubernetes, CI/CD, observability Autonomous; strong communication with technical and non-technical stakeholders
Preferred:
Prop trading, hedge fund, or financial services Firm-wide platform or standards work Multi-model environments (Claude, GPT, etc.) Agent evaluation and testing in production
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DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.
