Full Stack AI Software Engineer

🕒 il y a 2 mois

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🧑‍💻 Développeur Full-Stack

👻 Score fantôme 35%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Freedom Mortgage

Site WebLinkedInTous les Emplois

5001 - 10000 employés

Fondée en 1990

💸 Finance

🏠 Immobilier

👥 B2C

💰 €500 000 000 Debt Financing - Freedom Mortgage en 2025-08

Finance • Real Estate • B2C

Freedom Mortgage est un prêteur et gestionnaire de prêts hypothécaires résidentiels basé aux États-Unis qui offre des produits de prêts immobiliers et des services connexes aux consommateurs. L'entreprise propose des prêts hypothécaires pour l'achat et le refinancement (VA, FHA, USDA et conventionnels), des HELOCs, des termes à taux fixe et ajustable, des refinancements avec retrait de trésorerie et simplifiés, des outils de gestion de compte en ligne et de paiement, ainsi qu'un support client comprenant des conseillers en prêt. Freedom Mortgage se concentre sur l'origine et le service des prêts hypothécaires pour les consommateurs (B2C) pour les acheteurs de maison et les propriétaires.

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

🎯 Exigences

• 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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