Ai/Ml Engineer

AI/ML EngineerThe RoleWe are running an engagement to design and build an AI agent system that manages a complex, high-value transaction workflow for a large enterprise client, from initial engagement through close-out, across a multi-stage process.
As an AI/ML Engineer, you will build agent capabilities in parallel during the build phases, working under the Lead AI/Agent Architect. You will implement the tool integrations, data pipelines, and per-stage agent components that let a full transaction scenario run end to end against sandbox data.
Key Responsibilities
Per-Stage Agent Build: Implement agent capabilities for individual workflow stages (for example engagement agreement generation, needs-assessment brief, market survey and long-list scoring, tour management, RFP and proposal analytics, lease abstraction, and close-out and invoicing), building to the orchestration model and stage handoff protocols defined by the Lead Architect.
Tool & Integration Development: Build the typed tools the agents call: template population, market-data query, financial analytics (NER, TI, free rent, NPV), clause and lease-clause extraction, and document assembly.
Data Pipelines: Build and maintain pipelines against sandbox and representative sample data, including the property availability data source.
Human-in-the-Loop Implementation: Encode the approval gates and review checkpoints specified by the architect, so binding steps always route through a broker confirmation.
Quality & End-to-End Testing: Validate components against deal-scenario data and participate in end-to-end testing across all eight stages, checking artifact quality and stage handoff integrity.
Build-Phase Readiness: Participate in Phase 1 architecture workshops to ensure the build starts on solid foundations.
Required Skills and Experience
4+ years in software or machine learning engineering, with production experience building LLM-powered features or agents.
Agent Tooling: Hands-on experience with agent frameworks, tool and function calling, retrieval, and prompt engineering.
Python & Data Engineering: Strong Python and practical experience building data pipelines and integrating structured and unstructured data sources.
Document Processing: Comfort parsing, extracting, and generating documents across formats such as PDF, DOCX, and structured templates.
Financial & NLP Depth: Experience implementing financial analytics (lease economics, NPV, scenario modelling) and NLP information extraction (clause and entity extraction from contracts or leases) is strongly preferred.
Domain Exposure: Exposure to commercial real estate or another document-heavy transaction domain is a plus.
AI-Native Workflow: Comfort utilizing LLM code assistants and agentic engineering to ship faster and with higher quality.
Agile Execution: Ability to move quickly in hypothesis-driven, milestone-based sprint cycles, shipping working components and iterating against real evidence.
Employment type:
Contract
Work arrangement:
New York or US Eastern. We work in our clients' time zones, with regular time in person on client sites.
Compensation:
Compensation. A competitive salary.
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