Full Stack AI Software Engineer

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 10%

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Logo of Freedom Mortgage

Freedom Mortgage

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.

📋 Description

• Design, build, deploy, secure, and continuously improve enterprise software and AI-enabled applications • 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 with users, and iteratively release functionality • Build and enhance applications across frontend, backend, API, integration, data, and infrastructure layers • Design reusable services, components, APIs, workflows, and integration patterns • Implement AI capabilities using large language models, retrieval-augmented generation, embeddings, vector search, structured outputs, tool calling, multimodal models, and agentic workflows • Build secure AI agents interacting with applications, APIs, databases, documents, and enterprise systems • Develop prompts, system instructions, context-management strategies, tool definitions, workflows, and reusable AI skills • Evaluate models and implement evaluations, regression tests, guardrails, human-review controls, grounding, observability, and fallbacks • Identify and mitigate hallucination, prompt-injection, data-leakage, model-bias, unsafe-output, and unauthorized-tool-use risks • 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 deployment practices • Serve as accountable engineer or technical owner for up to three applications • Monitor availability, performance, capacity, security, errors, and user experience; diagnose and resolve incidents and defects • Perform maintenance, upgrades, vulnerability remediation, documentation, incident response, root-cause analysis, disaster-recovery testing, and business-continuity exercises • Recommend modernization, re-platforming, consolidation, or retirement of applications • Collaborate with Information Security, Enterprise Architecture, database, data-management, IT Support, infrastructure, cloud, network, identity, DevOps, QA, product, legal, risk, and compliance teams • Communicate technical decisions, constraints, risks, tradeoffs, progress, and recommendations to technical and nontechnical audiences • Follow software-development, change-management, security, architecture, data-governance, and release-management standards • Ensure legal, regulatory, privacy, records-management, accessibility, and industry compliance • Protect confidential, proprietary, customer, and regulated data • Review, test, and appropriately license AI-generated code and content • Contribute reusable engineering patterns, libraries, templates, prompts, skills, standards, and lessons learned • Mentor other engineers and improve AI-enabled software-delivery standards • Perform other related duties as assigned

🎯 Requirements

• Five or more years of professional software-engineering experience across the design, development, testing, deployment, and support of production applications • At least two to three years of professional experience engineering software 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 modern backend language, such as Python, Java, C#, Go, or TypeScript/Node.js • Strong proficiency with modern frontend development using JavaScript or TypeScript and a framework such as React, Angular, or Vue • Experience designing and consuming RESTful APIs, event-driven services, microservices, and enterprise integrations • Experience with relational databases, SQL, data modeling, and at least one modern nonrelational or vector-database technology • Practical experience integrating large language models 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-based source control, automated testing, code review, continuous integration, continuous delivery, 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, including authentication, authorization, encryption, secrets management, dependency management, and common application-security risks • Demonstrated ability to work directly with business users and convert business problems into working software • Strong analytical, troubleshooting, communication, collaboration, and documentation skills • Ability to independently manage multiple priorities and maintain ownership of up to three applications • Bachelor’s or master’s degree in computer science, software engineering, information systems, data science, artificial intelligence, or a related discipline, or equivalent practical experience • Experience building AI agents, retrieval-augmented generation solutions, semantic-search applications, document-processing systems, or workflow automation • Experience with model-evaluation frameworks, 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 working in a regulated industry such as financial services, mortgage lending, banking, insurance, healthcare, or government • Experience modernizing legacy applications and integrating them with cloud, data, and AI platforms • Certificates, Licenses, Registrations: None Required • Ability to comply with company policies and maintain regular and punctual attendance

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