Lead AI and Data Solution Engineer

U.S. Financial Technology • Remote,

7d • $200,000 - $215,000 • Remote

About The Position

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 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. The company provides best-in-class single-family issuance, bond administration, disclosure, and tax services, supporting a broad portfolio of products for clients with full lifecycle management. Their market-leading, cloud-based, end-to-end platform executes transactions on an extraordinary scale, bolstering liquidity in the secondary mortgage market. This role combines expertise in financial services with technology innovation.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 8+ years of experience in data engineering, AI solution development, or related roles.
• Proven expertise in large language models (LLMs), agentic AI systems, and Model Context Protocol (MCP).
• Good working experience developing and integrating AI solutions using AWS Bedrock, including prompt engineering, RAG, and enterprise application integration.
• Hands-on experience building AI applications using Python frameworks such as LangChain, LlamaIndex, FastAPI, and AWS/OpenAI SDKs.
• Strong experience with Snowflake and AWS services (Glue, S3, Lambda, SageMaker, etc.).
• Deep understanding of AI/ML frameworks, data pipelines, and cloud-native architectures.
• Hands-on experience with LLM deployment, fine-tuning, and integration.
• Advanced proficiency in Python programming with the ability to design, develop, test, and troubleshoot production-grade AI/ML applications and reusable frameworks.
• Proficiency in agentic AI design patterns and implementation.
• Expertise in Model Context Protocol (MCP) for context-aware model deployment and management.
• Strong knowledge of Snowflake, AWS, and advanced data modeling.
• Experience with data governance, security, and compliance best practices.
• Excellent communication, collaboration, and presentation skills.
• Ability to translate complex technical concepts for non-technical stakeholders.
• Applicants must be authorized to work in the US without requiring employer sponsorship currently or in the future. U.S. FinTech does not offer sponsorship for this position.

Nice To Haves

• Experience in the financial services or mortgage industry is preferred.

Responsibilities

• Lead the design, development, and deployment of enterprise-scale data and AI solutions, ensuring alignment with business objectives and technical best practices.
• Architect, implement, and optimize large language models and agentic AI workflows for business automation and decision support.
• 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.
• Develop, integrate, and manage MCP-based solutions to enhance model interpretability, context management, and deployment at scale.
• Leverage AWS and Snowflake to build scalable, secure, and efficient data pipelines for structured and unstructured data.
• Partner with cross-functional teams, including other technology, business, risk, legal, and compliance stakeholders, to deliver integrated solutions.
• Stay current with emerging technologies and industry trends in AI, data engineering, and cloud computing, driving continuous improvement and innovation.
• Ensure all solutions meet regulatory, security, and compliance requirements relevant to the financial services industry.
• Provide technical leadership and mentorship to junior team members.

Benefits

• performance bonus
• 401k match
• healthcare coverage
• PTO

What This Job Offers

• Job Type: Full-time
• Career Level: Senior