Lead AI and Data Solution Engineer

OVERVIEW

The Company

U.S. Financial Technology (U.S. FinTech) is seeking an experienced Lead AI and Data Solution Engineer to drive the development, integration, and deployment of advanced AI, data engineering, and cloud-based solutions. This is a full-time remote opportunity.

U.S. FinTech built and operates the largest and most advanced mortgage securitization platform in the world, supporting the Uniform Mortgage-Backed Security (UMBS) of Fannie Mae and Freddie Mac.

Supporting 70% of the mortgage-backed securities in the market, U.S. FinTech provides best-in-class single-family issuance, bond administration, disclosure, and tax services. We support a broad portfolio of products for our clients with full lifecycle management.

Our market-leading, cloud-based, end-to-end platform executes transactions on an extraordinary scale which has bolstered liquidity in the secondary mortgage market, one of the largest and most important financial markets in the world. Our unique approach to securitization combines the best minds in financial services with the know-how, flexibility, and innovation of leading technologists.

RESPONSIBILITIES

Job Information

The ideal candidate will have deep expertise in data engineering, agentic AI systems, large language models (LLMs), and Model Context Protocol (MCP). The preferred candidate will bring deep experience with AWS and Snowflake services, including a strong understanding of security best practices for cloud-based AI and data solutions. This role requires a hands-on leader who can design scalable, secure, and innovative data pipelines and AI solutions that deliver business value.

Key Job Functions

• Solution Engineering: Lead the design, development, and deployment of enterprise-scale data and AI solutions, ensuring alignment with business objectives and technical best practices.
• LLM and Agentic AI: Architect, implement, and optimize large language models and agentic AI workflows for business automation and decision support.
• Framework Expertise: Design and deploy AI solutions using leading frameworks such as LangChain, LangGraph, and n8n for scalable agent orchestration, workflow automation, and integration with business systems
• Model Context Protocol (MCP): Develop, integrate, and manage MCP-based solutions to enhance model interpretability, context management, and deployment at scale.
• Cloud and Data Engineering: Leverage AWS and Snowflake to build scalable, secure, and efficient data pipelines for structured and unstructured data.
• Collaboration: Partner with cross-functional teams, including other technology, business, risk, legal, and compliance stakeholders, to deliver integrated solutions.
• Innovation: Stay current with emerging technologies and industry trends in AI, data engineering, and cloud computing, driving