Full Stack AI Software Engineer

Role Description

We are seeking an exceptional Full-Stack AI Software Engineer to design, build, deploy, secure, and continuously improve enterprise software and AI-enabled applications. This is a hands-on engineering role for a highly capable product engineer who can translate complex business problems into secure, scalable, and intuitive technical solutions. The engineer will work directly with business stakeholders in an interactive, iterative development model—rapidly converting ideas into working prototypes, testing solutions with users in real time, and refining functionality until the intended business outcome is achieved. The successful candidate will combine strong traditional software-engineering fundamentals with practical experience using modern AI-assisted development tools, large language models, AI agents, and automation frameworks. The engineer will own applications throughout their lifecycle, including architecture, development, testing, deployment, monitoring, vulnerability remediation, maintenance, modernization, and retirement. Each engineer may be responsible for the health, delivery, and continued evolution of up to three applications at any given time.

Qualifications

• 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 in 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 a major cloud environment such as 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, understand workflows, challenge assumptions constructively, 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.

Requirements

• 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 frameworks or platforms such as 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.
• Understands how mortgage products, servicing operations, borrower experience, compliance, and technology intersect to create business value.
• Can effectively communicate with mortgage business stakeholders without requiring extensive business translation.
• Designs technology solutions that improve operational efficiency while maintaining compliance and reducing risk.
• 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 developing software in close collaboration with product designers, business operators, and end users.
• Demonstrated ability to improve development velocity without compromising engineering quality or operational stability.

Benefits

• Comply with all company policies and procedures.
• Maintain regular and punctual attendance.