AI Engineer: Autonomous Agents & Deployment

Millennium; New York (NY); On-site; USD 175,000 - 250,000; Full time

Job summary

Millennium seeks an innovative AI Engineer to advance agentic automation and predictive models within its Central AI team in New York. You will build scalable agent systems, integrate tools, and ensure reliable performance across business functions, from alpha capture to compliance.

The role emphasizes hands-on ML/LLM work, end-to-end project ownership, and collaboration with traders, CFOs, and other teams to turn research into production-ready capabilities.

Qualifications

• 3+ years shipping production software, ML, or AI systems; proven delivered work.
• Strong Python and engineering fundamentals; prototypes become products.
• Hands-on LLM and agent experience: tool use, orchestration, retrieval, evals.
• Supervised ML depth: training, validation, feature engineering, drift awareness.
• Comfort with messy/unknown data and quick functional fluency.
• Autonomy to embed with trader or CFO teams and own end-to-end problems.

Responsibilities

• Own agentic process automation: build agents with integrations and audits.
• Develop prediction/decision-support models using firm data.
• Create document intelligence pipelines for contracts, emails, transcripts.
• Build entity intelligence and self-improving systems with knowledge graphs.
• Collaborate with business teams from initial convo to deployment.
• Turn proven solutions into reusable capabilities for the firm.

Skills

Python

LLM & Agent Experience

ML systems

Structured outputs

Validation & Evaluation

Data wrangling

Education

Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative discipline

Job description

Millennium seeks an innovative AI Engineer to advance agentic automation and predictive models within its Central AI team in New York. You will build scalable agent systems, integrate tools, and ensure reliable performance across business functions, from alpha capture to compliance.

The role emphasizes hands-on ML/LLM work, end-to-end project ownership, and collaboration with traders, CFOs, and other teams to turn research into production-ready capabilities.