Lead AI Engineer

Required Skills & Experience

Qualifications

• 5+ years of software engineering experience, including recent work deploying LLM-based systems in production
• Track record of building and maintaining internal tools or products with active users
• Financial services or real estate experience preferred Required Technical Skills
• Strong proficiency in Python
• Advanced SQL and experience with relational databases such as PostgreSQL or SQL Server
• Hands-on experience building with LLM APIs (Anthropic, OpenAI or similar), including structured outputs, tool use and prompt evaluation
• Experience extracting data from PDFs, scanned documents and spreadsheets using OCR and LLM-based methods
• Experience deploying and running applications on AWS, Azure or GCP
• Building and integrating REST APIs
• Git, CI/CD and containerization (Docker)

Nice to Have Skills & Experience

Preferred Technical Skills

• TypeScript and React for building internal user interfaces
• Agent frameworks and protocols such as LangGraph or MCP
• Vector search and retrieval (pgvector, Pinecone or similar)
• Data warehouse and transformation tools such as Snowflake, Databricks or dbt
• Integration with Microsoft 365, SharePoint and Excel-based workflows
• Experience with CRM, loan origination or loan servicing platforms
• Observability and evaluation tooling for LLM applications

Job Description

Overview

Insight Global is seeking a lead AI engineer based in New York, NY or Miami, FL. The Lead AI Engineer will lead the design and development of AI-driven software across the client's lending and servicing platform. Reporting directly to the COO, this individual will build and maintain the tools, automations and data infrastructure that improve how the business operates and will guide the company's broader use of AI. The ideal candidate is an experienced engineer who has AI systems and can work closely with business teams to understand where technology can make a real difference at a leading commercial real estate finance company.

Roles & Responsibilities Engineering & Delivery

• Design, build and maintain internal applications and agents that support originations, underwriting, servicing, asset management and operations
• Develop pipelines that extract and structure data from loan files, rent rolls, operating statements and third-party reports
• Build out the internal infrastructure for deploying and supporting AI tools, including model access, evaluation and monitoring
• Identify manual processes across the business and develop automated solutions to replace them
• Establish standards for reliability, security and responsible use as the platform grows Collaboration & Adoption
• Work closely with leaders across the business to develop a deep understanding of how the company operates and where AI can improve efficiency
• Partner with the business technology and data analytics teams to integrate new systems with existing platforms and data sources
• Lead adoption of new tools across teams, including training and ongoing support
• Advise leadership on AI priorities and emerging capabilities based on hands-on experience building at the company