AI Architect - NYC, NY - Remote (Candidates only from NY / NJ)

Overview

$DOE
Full Time
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - term contract

Skills

AI
ML
LLM
RAG
Azure OpenAI
AI Architect

Job Details

Job Title: AI Architect

Location: NYC, NY - Remote (Candidates only from NY / NJ)

Duration: Long-term contract

Relevant Experience: 15+ Years

  • AI Architect to lead the design and implementation of enterprise-scale AI solutions for financial services automation.
  • Drive architectural decisions for LLM-based systems, agentic workflows, and intelligent document processing platforms serving private equity and fund management operations.

Required Qualifications:

  • 15+ years of experience in AI/ML architecture with 8+ years in enterprise AI solutions.
  • Deep expertise in LLM architectures, prompt engineering, and agentic frameworks (Lang Graph, LangMem).
  • Hands-on experience with Azure OpenAI GPT-4/5, embedding models, and Azure cloud services.
  • Strong background in Python, distributed systems, and enterprise architecture.
  • Experience with Claude Code for agentic coding and AI-powered development.
  • Proven track record in financial services or regulatory compliance environments.
  • Expert knowledge of RAG architectures, advanced RAG patterns, and vector database optimization.
  • Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP).
  • Proven ability to architect and scale AI solutions for enterprise workloads (1M+ documents, sub-second response times).

Key Responsibilities

  • Design end-to-end AI solutions for private equity fund operations and financial automation.
  • Architect scalable agentic AI frameworks using LangGraph, LangMem, and custom agent orchestration.
  • Lead technical strategy for Azure OpenAI GPT-5 integration and advanced embedding-based retrieval systems.
  • Design and implement advanced RAG architectures, including hybrid search, query routing, and contextual retrieval.
  • Establish multi-agent systems with Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP).
  • Architect Small Language Model (SLM) integration for specialized tasks and cost optimization.
  • Design enterprise-scale solutions supporting millions of documents with sub-second query response times.
  • Establish AI governance, model safety protocols, and regulatory compliance frameworks.
  • Lead architectural reviews for distributed AI systems, micro services, and cloud-native deployments.
  • Hands-on development using Claude Code for rapid prototyping and agentic workflows.
  • Drive architectural reviews for LlamaParse/Azure Document Intelligence integration.
  • Design fault-tolerant, high-availability AI systems with automatic failover and load balancing.
  • Establish comprehensive monitoring, observability, and performance optimization strategies.
  • Mentor technical teams and establish AI engineering best practices using modern toolchains.
  • Oversee model performance evaluation using LangGraph evals and DeepEval frameworks.
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