Saaf Finance is building the AI workforce for the mortgage industry. We are an AI startup integrated with a top-10 mortgage lender, American Heritage Lending (AHL). Together we are combining AHL’s 15+ years of mortgage origination expertise with the power of AI-native innovation to redefine what’s possible in mortgage lending.
As a Full Stack Engineer at Saaf Finance, you will design and ship software that automates complex mortgage workflows while collaborating closely with founders, engineers, and design. We are an AI-native engineering team: AI-assisted development tools are a regular part of how we build, review, and ship software. We expect engineers to use these tools thoughtfully and effectively as part of their daily workflow.
5+ years of experience as a Full Stack Developer, with experience spanning both frontend and backend development.
3+ years of experience working with frontend JavaScript frameworks such as React or Angular, and backend technologies like NodeJS (these may overlap).
Strong experience designing and implementing APIs (RESTful and/or GraphQL), including versioning, documentation, and security best practices.
Demonstrated, regular use of AI-powered development tools (e.g., Cursor, GitHub Copilot, Claude Code, or similar) to accelerate coding, debugging, or documentation workflows.
Proficiency in SQL and NoSQL databases such as Postgres, MongoDB, or MySQL.
Solid understanding of the software development life cycle and Agile methodologies.
Proven experience leading a team or architecting a large-scale enterprise product.
Exceptional problem-solving, debugging, and software design skills.
Excellent written and verbal communication skills.
Self-driven with a strong work ethic and passion for excellence.
Ability to work effectively both independently and as part of a team.
Strong understanding of AWS infrastructure and hands-on experience with services such as Serverless Framework, Lambda, and CloudFormation.
Experience working with Terraform.
Experience with prompt engineering for code generation, refactoring, test creation, or building AI-powered product features.
Knowledge of design patterns, data structures, and distributed systems.
Experience with data engineering (pipelines, ETL workflows, data architecture).
Prior early-stage startup experience is highly preferred.
