
5001 - 10000 employees
Founded 1990
💸 Finance
🏠 Real Estate
👥 B2C
💰 $500M Debt Financing - Freedom Mortgage on 2025-08
Finance • Real Estate • B2C
Freedom Mortgage is a U. S. -based residential mortgage lender and servicer that provides home loan products and related services to consumers. The company offers purchase and refinance mortgages (VA, FHA, USDA, and conventional), HELOCs, fixed- and adjustable-rate terms, cash-out and streamline refinances, online account management and payment tools, and customer support including loan advisors. Freedom Mortgage focuses on consumer (B2C) mortgage origination and servicing for homebuyers and homeowners.
🕒 August 10
Angular
AWS
Azure
Cloud
Distributed Systems
Google Cloud Platform
Java
JavaScript
Kubernetes
Microservices
Node.js
Python
React
SQL
TypeScript
Vue.js
Go
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5001 - 10000 employees
Founded 1990
💸 Finance
🏠 Real Estate
👥 B2C
💰 $500M Debt Financing - Freedom Mortgage on 2025-08
Finance • Real Estate • B2C
Freedom Mortgage is a U. S. -based residential mortgage lender and servicer that provides home loan products and related services to consumers. The company offers purchase and refinance mortgages (VA, FHA, USDA, and conventional), HELOCs, fixed- and adjustable-rate terms, cash-out and streamline refinances, online account management and payment tools, and customer support including loan advisors. Freedom Mortgage focuses on consumer (B2C) mortgage origination and servicing for homebuyers and homeowners.
• Partner with business stakeholders to identify problems, define outcomes, and engineer technical solutions • Translate business needs into requirements, technical designs, user stories, acceptance criteria, and production-ready software • Rapidly prototype, demonstrate, test, and iteratively release solutions with users • Build and enhance full-stack applications across frontend, backend, APIs, integrations, data, and infrastructure • Design and implement AI-enabled capabilities using LLMs, RAG, embeddings, vector search, tool calling, multimodal models, and agentic workflows • Build secure AI agents that interact with applications, APIs, databases, documents, and enterprise systems • Develop prompts, system instructions, context-management strategies, tools, workflows, and reusable AI skills • Evaluate models and implement evaluations, regression tests, guardrails, human-review controls, grounding, observability, and fallback mechanisms • Own software delivery from discovery and architecture through development, testing, deployment, production support, and continuous improvement • Write clean, modular, testable, secure, and documented production code • Develop and maintain automated unit, integration, API, UI, regression, performance, security, and end-to-end tests • Build and maintain CI/CD pipelines and release software through safe, observable, reversible deployments • Serve as accountable engineer or technical owner for up to three applications • Monitor application availability, performance, capacity, security, errors, and user experience • Diagnose production incidents and perform maintenance, upgrades, vulnerability remediation, and technical-debt reduction • Maintain application documentation, runbooks, architecture diagrams, deployment instructions, and recovery procedures • Participate in incident response, root-cause analysis, disaster-recovery testing, and business-continuity exercises • Collaborate with information security, enterprise architecture, data-management, infrastructure, cloud, network, identity, DevOps, QA, product, legal, risk, and compliance teams • Ensure compliance with software-development, security, architecture, data-governance, privacy, accessibility, records-management, and release-management standards • Contribute reusable engineering patterns, libraries, templates, prompts, skills, and development standards • Mentor engineers and help improve AI-enabled software delivery standards
• Five or more years of professional software-engineering experience across design, development, testing, deployment, and support of production applications • At least two to three years of professional experience using modern AI-assisted engineering tools and AI development practices • Demonstrated ability to build and support full-stack applications from concept through production • Strong proficiency in at least one backend language: Python, Java, C#, Go, or TypeScript/Node.js • Strong proficiency in JavaScript or TypeScript and a frontend framework such as React, Angular, or Vue • Experience with RESTful APIs, event-driven services, microservices, and enterprise integrations • Experience with relational databases, SQL, data modeling, and a nonrelational or vector database • Practical experience integrating LLMs or generative-AI services into production or enterprise applications • Experience with AI coding tools such as Cursor, Claude Code, GitHub Copilot, OpenAI Codex, or comparable platforms • Experience with Git, automated testing, code review, CI/CD, and modern DevOps practices • Experience deploying and operating applications in AWS, Microsoft Azure, or Google Cloud Platform • Working knowledge of containers, infrastructure as code, observability, application security, and vulnerability remediation • Strong understanding of secure software-development principles, authentication, authorization, encryption, secrets management, dependency management, and application-security risks • Ability to work directly with business users and convert business problems into working software • Strong analytical, troubleshooting, communication, collaboration, and documentation skills • Ability to manage multiple priorities and own up to three applications • Bachelor’s or master’s degree in computer science, software engineering, information systems, data science, artificial intelligence, or related discipline, or equivalent practical experience • Experience with AI agents, RAG, semantic search, document processing, workflow automation, model evaluation, prompt testing, AI observability, red-team testing, and responsible-AI controls • Experience with LangGraph, Semantic Kernel, OpenAI Agents SDK, model context protocol, or comparable orchestration technologies • Experience with Kubernetes, serverless architectures, messaging platforms, API gateways, and distributed systems • Experience in a regulated industry such as financial services, mortgage lending, banking, insurance, healthcare, or government • Familiarity with privacy, model risk, information security, records retention, accessibility, and regulatory compliance requirements • Experience modernizing legacy applications and integrating them with cloud, data, and AI platforms • Experience collaborating with product designers, business operators, and end users • Certificates, licenses, and registrations: None required
• Remote work arrangement • Equal employment opportunities • Reasonable accommodations for disabilities • Opportunity to work on modern AI-enabled software and enterprise applications
Apply Now🕒 August 10
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