U.S. Financial Technology

Design and implement enterprise-scale data management and integration solutions using modern cloud-based data platforms and tools. | Minimum 5 years in data-driven solutions, 3+ years with AWS, expertise in real-time data solutions, scripting in Python and SQL, and experience with cloud data warehouses. | OVERVIEW The Company U.S. Financial Technology (U.S. FinTech) is seeking an experienced Senior Data/AI Engineer to join our team of talented professionals. 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 Data/AI Engineer will be responsible for solution engineering of enterprise scale data management best practices. This includes patterns such as modern data integration frameworks and building of scalable distributed systems using emerging cloud-based data design patterns. This role will be responsible for developing data integration tasks in the data and analytics space. This position will report to the Director of Data Management under Data & AI organization. Key Job Functions Demonstrate ability in implementing data warehouse solutions using modern data platforms such as Snowflake, Databricks or Redshift. Build data integration solutions between transaction systems and analytics platforms. Expand data integration solutions to ingest data from internal and external sources and to further transform as per the business consumption needs. Develop tasks for a multitude of data patterns, e.g., real-time data integration, advanced analytics, machine learning, BI and reporting. Fundamental understanding of building of data products by data enrichment and ML. Act as a team player and share knowledge with the existing team members. QUALIFICATIONS Education Bachelor’s degree in computer science or a related field. Minimum Experience Minimum 5 years of experience in building data driven solutions. At least 3 years of experience working with AWS services. Applicants must be authorized to work in the US without requiring employer sponsorship currently or in the future. U.S. FinTech does not offer H-1B sponsorship for this position. Specialized Knowledge & Skills Expertise in real-time data solutions, good-to-have knowledge of streams processing, Message Oriented Platforms and ETL/ELT Tools. Strong scripting experience using Python and SQL. Working knowledge of foundational AWS compute, storage, networking and IAM. Understanding of Gen AI models, prompt engineering, RAG, fine tuning and pre-tuning will be a plus. Solid scripting experience in AWS using Lambda functions. Knowledge of CloudFormation template preferred. Hands-on experience with popular cloud-based data warehouse platforms such as Redshift and Snowflake. Experience in building data pipelines with related understanding of data ingestion, transformation of structured, semi-structured and unstructured data across cloud services. Knowledge and understanding of data standards and principles to drive best practices around data management activities and solutions. Experience with one or more data integration tools such as Attunity (Qlik), AWS Glue ETL, Talend, Kafka etc. Strong understanding of data security – authorization, authentication, encryption, and network security. Hands on experience in using and extending machine learning framework and libraries, e.g, scikit-learn, PyTorch, TensorFlow, XGBoost etc. preferred. Experience with AWS SageMaker family of services or similar tools to develop machine learning models preferred. Strong written and verbal communication skills to facilitate meetings and workshops to collect data, functional and technology requirements, document processes, data flows, gap analysis, and associated data to support data management/governance related efforts. Acts with integrity and proactively seeks ways to ensure compliance with regulations, policies, and procedures. Demonstrated ability to be self-directed with excellent organization, analytical and interpersonal skills, and consistently meet or exceed deadline deliverables. Strong understanding of the importance and benefits of good data quality, and the ability to champion results across functions. Pay Range $141,750 to $165,000 U.S. FinTech's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) a candidate’s qualifications, skills, competencies, and experience, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law. U.S. FinTech offers a competitive total compensation package, which includes a performance bonus, 401k match, healthcare coverage, PTO, and a broad range of other benefits. Employment As a condition of employment with U.S. Financial Technology, any successful job applicant will be required to successfully complete a background investigation, which may also include a credit check for positions in some areas of our business. U.S. Financial Technology is an Equal Opportunity Employer. ##LI-Remote

Design and deploy enterprise-scale AI and data solutions, including LLMs, agentic AI workflows, and MCP-based systems, leveraging AWS and Snowflake. | Minimum 8+ years in data engineering or AI solution development, with expertise in LLMs, agentic AI, MCP, AWS Bedrock, Snowflake, and financial industry experience preferred. | 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 continuous improvement and innovation. Governance and Compliance: Ensure all solutions meet regulatory, security, and compliance requirements relevant to the financial services industry. Mentorship: Provide technical leadership and mentorship to junior team members. QUALIFICATIONS Education Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Minimum Experience 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. Strong experience with Snowflake and AWS services (Glue, S3, Lambda, SageMaker, etc.). Experience in the financial services or mortgage industry is preferred. Applicants must be authorized to work in the US without requiring employer sponsorship currently or in the future. U.S. FinTech does not offer H-1B sponsorship for this position. Specialized Knowledge & Skills Deep understanding of AI/ML frameworks, data pipelines, and cloud-native architectures. Hands-on experience with LLM deployment, fine-tuning, and integration. 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. Pay Range $200,000 to $215,000 U.S. FinTech's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) a candidate’s qualifications, skills, competencies, and experience, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law. U.S. FinTech offers a competitive total compensation package, which includes a performance bonus, 401k match, healthcare coverage, PTO, and a broad range of other benefits. Employment As a condition of employment with U.S. Financial Technology, any successful job applicant will be required to successfully complete a background investigation, which may also include a credit check for positions in some areas of our business. U.S. Financial Technology is an Equal Opportunity Employer. ##LI-Remote