AI Engineer

Millennium•New York, NY

2d•$175,000 - $250,000

About The Position

The Market Data Operations (MD Ops) function is a centralized team that manages all aspects of data related vendor services for the firm. Their mandate is both commercial (cost, contracts) and operational (entitlements, access, compliance). In this seat, you’ll be within the core AI engineering team shipping AI products that ingests unstructured contracts, extract key terms into structured, tie them to entitlements and invoices, and provide a front end with monitoring and controls for day‑to‑day operations.

Requirements

Bachelor’s degree in Computer Science or a related field.
5+ years of professional experience with Python, including building production services (Django, Flask, or FastAPI).
Experience working with unstructured documents (contracts, PDFs, legal docs) and turning them into structured data.
Prompt engineering and working with structured JSON outputs
Comfort wiring models into real applications (tool/MCP‑style integrations, APIs).
Experience using cloud platform, ideally AWS.
Able to define and track quantitative metrics for AI features (accuracy, latency, cost, etc.).
Strong communication skills and comfortable working directly with non‑technical users.
Enjoys a start‑up‑like environment inside a large firm: small team, high ownership, fast iteration.

Nice To Haves

Experience building AI solutions in financial services, especially around market data, vendor management, or legal/contract workflows.
Familiarity with entitlements/governance and large internal data platforms (e.g., a Market Data Warehouse).

Responsibilities

Build the core application and workflow agents for Market Data Operations in Python; integrate with AWS and internal systems like the Market Data Warehouse.
Ingest and understand contracts at scale, using LLMs to extract costs, fee schedules, entitlements, renewal terms, and payment details.
Connect the dots between contracts, entitlements, invoices, and payments so Ops, Legal, and Finance can see a single “source of truth” and catch issues early.
Design and tune LLM workflows (prompt engineering, tool/MCP integration, structured outputs) for contract Q&A, summarization, and exception flagging.
Own monitoring and controls for the AI system: logging, metrics, guardrails, and human‑in‑the‑loop review to keep performance, reliability, and quality high.
Work directly with stakeholders (Market Data Ops, analysts, Legal, Finance/AP) to understand their workflows and quickly iterate on features that actually get used.

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