AI Engineer

Description

  

• Develop end-to-end Generative AI solutions, from data ingestion to production deployment, with a focus on mortgage industry applications.
• Fine-tune, evaluate, and optimize large language models (LLMs) for use cases such as automated document classification, loan condition generation, and borrower communication support.
• Integrate AI into enterprise workflows to automate routine tasks, enhance underwriting decision support, and improve broker and borrower engagement.
• Design and implement RAG pipelines using vector databases to power intelligent knowledge search for guidelines, pricing, and compliance references.
• Leverage Azure AI Foundry, AI Services, Model Catalog, Agents, Guardrails, and App Services to deliver secure, scalable AI tools for lending operations.
• Apply emerging AI research and tools where they create measurable value in loan processing, compliance monitoring, and risk assessment.
• Ensure AI solutions align with MLOps best practices, emphasizing scalability, maintainability, and regulatory compliance.
• Collaborate with Operations, Compliance, and IT teams to identify automation opportunities and drive AI adoption across the organization.
• Develop, document, and refine prompt engineering strategies and multi-agent system workflows for mortgage-specific applications.
• Maintain strict adherence to industry regulations, security protocols, and data governance requirements.

Requirements

  

• Ability to independently execute the complete AI solution development lifecycle.
• Hands-on experience with large language models (preferably Azure OpenAI) and frameworks such as LangChain or Semantic Kernel.
• Practical expertise with Azure AI Foundry, AI Services, Model Catalog, Agents, Guardrails, and App Services.
• Strong Python programming skills and familiarity with machine learning engineering best practices.
• Proven track record of transitioning AI solutions from prototype to production in enterprise environments.
• Experience with vector databases and RAG architectures.
• Cloud AI expertise (Azure or AWS) with a strong understanding of infrastructure and deployment strategies.
• Familiarity with prompt engineering, multi-agent systems, and advanced LLM orchestration.
• Understanding of MLOps, AI security, and compliance in regulated industries; mortgage or financial services industry experience is a plus.