Lorven Technologies

Compensation

Full Description

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.