Gen AI Engineer with Production Support, Python, LLM, RAG, 12+ Mths Cont, NYC, NY

Gen AI Engineer with Production Support, Python, LLM, RAG, 12+ Mths Cont, NYC, NY

JPC - 3592

Level 3 : (7+ yrs of total exp)

Loc: NYC, NY ( Hybrid, 3 days Onsite, Locals Preferred)

Dur: 12+ Mths Contract ( Might go Perm)

Role: Gen AI Engineer with Production Support, Python, LLM, RAG, Codex 12+ Mths Cont, NYC, NY

Description:

Consultant Description:

Applied AI Engineer

Overview

Fixed Income Credit Complex team is building an enterprise-grade GenAI workflow platform to power document intelligence, embedded productivity assistants, and automated business workflows across Institutional Securities. This is a production engineering role, not a research or prototype track. We are seeking senior, hands-on engineers who have designed, built, and operated GenAI systems in production environments. This role contributes to a shared platform used across business lines, with a clear path to owning core GenAI capabilities and standards within Institutional Securities.

What You'll Do

Design and evolve reusable GenAI workflow primitives and services used across Institutional Securities workflows.

Develop AI-powered assistants embedded into core Institutional Securities applications, leveraging agentic and tool-driven workflows.

Define and guide GenAI architecture decisions, including model selection, orchestration patterns, and evaluation strategies.

Establish and evolve LLMOps practices, including evaluation harnesses, prompt/version management, monitoring, and regression testing.

Design and implement controls for entitlements, data security, and PII handling, including usage of open-source models in regulated environments.

Partner with business and platform teams to drive adoption of shared GenAI capabilities across systems and workflows.

What You'll Bring

2+ years of hands-on experience building and operating GenAI systems in production

7+ years of full-stack or platform engineering experience, with strong proficiency in Python.

Proven experience designing and operating LLM-based systems using patterns such as RAG, tool/function calling, agentic workflows, and structured outputs.

Strong expertise in LLMOps, including evaluation frameworks, prompt/version management, regression testing, observability, and production reliability.

Experience building AI-first document ingestion and extraction pipelines with measurable quality and accuracy.

Experience with coding agents (Claude code, Codex, AMP, CoPilot)

Advanced experience in retrieval systems, including multi-stage pipelines, vector search, re-ranking, metadata filtering, and evaluation metrics (e.g., recall/precision tradeoffs, MRR, NDCG).

Practical experience debugging and stabilizing systems through real-world failure scenarios, including model regressions, prompt drift, retrieval degradation, and data quality issues.

Nice to Have

• Experience in Fixed Income, Credit, or broader Institutional Securities workflows.
• Familiarity with enterprise data governance, security models, and entitlements frameworks.
• Experience designing reusable internal platforms or shared developer tooling.