Position : AI Engineer — GenAI Platform

Duration : 6 -12 Months contract

Location : NYC/NY — Hybrid, 3 days onsite

Interview : Video then F2F in NYC .

Glider Assessment (Y): Python Glider .Local candidates only

Overview

We are seeking senior, hands-on full-stack engineers who have designed, built, and operated GenAI systems in production — and who treat failure modes, evaluation, and governance as first-class concerns. The role is a hands-on technical expert seat with a clear path to becoming a platform owner responsible for shared GenAI standards across Lending.

What You'll Do

Design and evolve reusable GenAI workflows used across Lending business lines.
Build an enterprise-grade AI document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review.
Develop AI-powered assistants embedded in Lending systems using agentic workflows.
Deliver automated content and deck generation workflows for reporting and approvals.
Advise on GenAI architecture: model selection, orchestration patterns, and evaluation strategy.
Establish LLMOps practices covering extraction accuracy, assistant reliability, prompt management, and audit monitoring.
Design and implement controls for entitlements and PII handling, including safe use of open-source models in a regulated environment.

What You'll Bring

5+ years of front-to-back engineering experience in Python or Java, with a focus on AI/ML platforms and workflows.
2+ years of dedicated, practical GenAI experience in an enterprise business environment, including designing and operating orchestration frameworks in production beyond vendor examples (e.g., custom LangChain-based systems).
Proven experience building and operating production-grade GenAI/LLM platforms applying RAG, tool/function calling, agentic workflows, and validated structured outputs.
Strong LLMOps expertise: evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production.
Hands-on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability.
Advanced retrieval depth: multi-vector and late-interaction approaches (e.g., ColBERT), chunking strategy, multi-stage retrieval pipelines, metadata filtering, and re-ranking — plus a working command of evaluation metrics (recall vs. precision, latency vs. quality, MRR, NDCG) and how they shape RAG design.
Experience operating GenAI systems through real production failures — model regressions, retrieval degradation, prompt drift, data quality issues — and designing mitigations.

Nice to Have

Fixed Income or Institutional Lending domain experience.
Experience in regulated environments with strong audit and control requirements.
Familiarity with enterprise security, data governance, and entitlement models.
Experience building reusable internal platforms or shared developer tooling.
Frontend experience (Angular or React).

Need LOCAL - AI Engineer in NYC NY - HYBRID

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