Forward Deployment AI Engineer

Millennium•New York, NY

1d•$175,000 - $250,000•Onsite

About The Position

Central AI sits within Millennium’s Information Technology organization, where flexible, scalable technology and advanced proprietary systems are core to the health and growth of the business, including the development of the next generation of analytical and trading capabilities. The Central AI team carries a broad mandate: bring AI to every function that runs the firm, spanning business development, alpha capture, execution services, risk management, finance, operations and middle office, legal, compliance, and recruiting. When a business team has a problem AI can solve, Central AI determines the right approach and ships the solution. You own everything from that conversation through architecture, deployment, evaluation, and iteration, then turn what works into reusable capabilities for the whole firm. Finance experience is not require, and in this seat you’ll rapidly deploy agents and provide analysis on the edge cases as opposed to solely focus on cherry picked projects.

Requirements

3+ years shipping production software, ML, or AI systems (flexible for exceptional builders; what you’ve shipped matters more than years served).
Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline.
Strong Python and engineering fundamentals; your prototypes become products others build on.
Substantial hands-on LLM and agentic experience: tool use, orchestration, structured outputs, retrieval, evals, and calibrated judgment about what agents can reliably do.
Supervised ML depth: training, validation, feature engineering, and awareness of pitfalls like leakage, overfitting, and drift.
Comfort with messy, heterogeneous data and unfamiliar domains, with the ability to become functionally fluent within days and earn credibility with subject-matter experts.
The autonomy to embed with a trader’s team or a CFO’s team, understand their world, and build without waiting for a spec.

Responsibilities

Own agentic process automation: reverse-engineer manual, undocumented workflows and build agents that execute them reliably, including tool integrations, orchestration, human-in-the-loop checkpoints, state management, and auditability.
Build prediction and decision-support models: forecasting, anomaly detection, ranking, matching, and classification over years of accumulated firm data, with proper validation and monitoring.
Develop document intelligence pipelines for extraction, classification, and review across contracts, filings, emails, and transcripts.
Build entity intelligence and self-improving systems, including knowledge graphs, entity resolution, enrichment pipelines, and eval/feedback loops that improve deployed systems over time.
Embed directly with business teams to scope problems end-to-end, owning everything from the initial conversation through architecture, deployment, evaluation, and iteration.
Turn proven solutions into reusable capabilities for the broader firm.