Senior Software Engineer

AmeriSave Mortgage Corp.

5d•$150,000 - $180,000•Remote

About The Position

AmeriSave Mortgage Corporation is a fintech lender focused on modernizing consumer lending through technology, automation, and AI-driven solutions. The Senior Software Engineer designs, develops, and maintains scalable web applications in a microservice environment, collaborating with cross-functional teams to deliver features and maintain application performance, quality, and stability. The position works in the CST timezone and supports remote collaboration. The role also builds and deploys AI-powered applications, integrates AI services into full-stack solutions, and contributes to semantic search, vector databases, and AI-enhanced user experiences. It involves working with unstructured and multimodal data and applying LLMOps practices such as prompt versioning, caching, observability, and cost tracking. Remote work requires high-speed Cable or Fiber internet with Ethernet connectivity. Minimum speeds are 70/30 Mbps for basic use, 200–300/35–70 Mbps for shared use, or 500–1,000/100+ Mbps for heavy use. The stated annual salary range is $150,000–$180,000.

Requirements

At least 5 years of professional experience in full-stack development.
Proficiency in HTML, CSS, and DOM manipulation for frontend development.
Strong experience with Node.js and Java for backend development.
Expertise in TypeScript for frontend and backend development.
Solid understanding of MS SQL, including database design, querying, and optimization.
Familiarity with modern web development practices and tools.
Experience integrating AI APIs such as OpenAI, Hugging Face, or Mistral.
Understanding of LLMs, prompt engineering, Cursor, and other AI orchestration frameworks.
Strong analytical and problem-solving skills.
Excellent communication and teamwork skills, including the ability to work effectively in a remote environment.
Attention to detail when handling evolving requirements and service stability.
For remote work, high-speed Cable or Fiber internet and Ethernet connectivity are required; minimum speeds are 70/30 Mbps (basic), 200–300/35–70 Mbps (shared), or 500–1,000/100+ Mbps (heavy use).

Nice To Haves

Experience with other frontend frameworks or libraries, including micro frontends.
Familiarity with Redis and pub/sub concepts.
Familiarity with containerization technologies such as Docker.
Knowledge of cloud platforms, preferably Azure.
Experience with CI/CD pipelines and DevOps practices.
Experience with AI-enhanced UI/UX design and intelligent user flows.
Exposure to vector databases, semantic search, and AI observability tools.
Experience with a leading Mortgage LOS and custom software platforms.
Expertise and hands-on experience with Aloha software.
Familiarity with mortgage compliance frameworks such as HMDA, TRID, RESPA, and ECOA.

Responsibilities

Design, develop, and maintain robust, scalable web applications using TypeScript, HTML, CSS, Java, and Node.js in a microservice environment.
Collaborate with cross-functional teams to define, design, and quickly ship new features.
Write clean, maintainable, and efficient TypeScript and Java code.
Optimize applications for speed and scalability.
Troubleshoot and debug applications to maintain optimal performance.
Implement data storage solutions using MS SQL and ensure data integrity.
Participate in code reviews to maintain code quality and best practices.
Stay current with industry trends and technologies and bring innovative solutions to the team.
Work in the CST timezone to support collaboration with the team.
Design and develop user interfaces using HTML and CSS and/or interfaces generated by JSON.
Perform DOM manipulation to create dynamic, interactive web pages.
Ensure web applications are cross-browser compatible and responsive.
Build and deploy AI-powered applications using LLMs, GenAI agents, and RAG pipelines.
Integrate AI services into full-stack solutions using frameworks such as LangChain, FastAPI, or Azure OpenAI.
Handle unstructured data, including PDFs, HTML, audio, and images, and work with multimodal models.
Implement LLMOps practices, including prompt versioning, caching, observability, and cost tracking.
Collaborate with AI/ML engineers and data scientists to embed intelligent automation and decisioning into enterprise workflows.
Contribute to semantic search, vector databases, and AI-enhanced user experiences.