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 artificial-intelligence-assisted engineering tools and artificial-intelligence 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-artificial-intelligence services into production or enterprise applications.
Experience with artificial-intelligence 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 Amazon Web Services, 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.
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.
Responsibilities
Partner directly with business stakeholders to understand operating processes, identify root problems, define measurable outcomes, and engineer effective technical solutions.
Translate ambiguous business needs into clear functional requirements, technical designs, user stories, acceptance criteria, and production-ready software.
Work interactively with users through rapid prototyping, demonstrations, feedback sessions, and iterative releases.
Build new applications and enhance existing platforms across the frontend, backend, application programming interface, integration, data, and infrastructure layers.
Develop intuitive, accessible, responsive, and high-performing user experiences.
Design reusable services, components, APIs, workflows, and integration patterns.
Make build-versus-buy and configuration-versus-custom-development recommendations.
Balance delivery speed with security, reliability, maintainability, scalability, and long-term architectural integrity.
Use modern artificial-intelligence engineering tools throughout the software development lifecycle to improve development speed, quality, testing, documentation, and maintainability.
Design and implement artificial-intelligence-enabled capabilities using large language models, retrieval-augmented generation, embeddings, vector search, structured outputs, tool calling, multimodal models, and agentic workflows.
Build artificial-intelligence agents that can securely interact with applications, APIs, databases, documents, and enterprise systems.
Develop prompts, system instructions, context-management strategies, tool definitions, workflows, and reusable artificial-intelligence skills.
Evaluate and select models based on accuracy, latency, security, cost, reliability, and business requirements.
Implement model evaluations, regression tests, guardrails, human-review controls, grounding, observability, and fallback mechanisms.
Identify and mitigate hallucination, prompt-injection, data-leakage, model-bias, unsafe-output, and unauthorized-tool-use risks.
Measure artificial-intelligence solutions using quality, accuracy, safety, performance, adoption, and business-value metrics.
Own software delivery from initial discovery and architecture through development, testing, deployment, production support, and continuous improvement.
Write clean, modular, testable, secure, and well-documented production code.
Develop and maintain unit, integration, application programming interface, user-interface, regression, performance, security, and end-to-end automated tests.
Use artificial-intelligence-assisted testing and automation tools while independently validating generated code and test results.
Participate in peer reviews, design reviews, architecture reviews, threat modeling, and release-readiness assessments.
Build and maintain continuous integration and continuous delivery pipelines.
Release software through safe, incremental, observable, and reversible deployment practices.
Ensure functional requirements and acceptance criteria are demonstrably satisfied before production release.
Serve as the accountable engineer or technical owner for up to three assigned applications.
Monitor application availability, performance, capacity, security, errors, and user experience.
Diagnose and resolve production incidents, defects, integration failures, and performance issues.
Perform maintenance, framework and dependency upgrades, operating-system or platform updates, certificate renewals, configuration changes, and technical-debt remediation.
Patch application and infrastructure vulnerabilities within established remediation timelines.
Maintain application documentation, support procedures, runbooks, architecture diagrams, data-flow diagrams, deployment instructions, and recovery procedures.
Participate in incident response, root-cause analysis, corrective-action planning, disaster-recovery testing, and business-continuity exercises.
Recommend modernization, re-platforming, consolidation, or retirement when an application no longer meets business or technical standards.
Implement secure coding standards, identity and access controls, encryption, secrets management, vulnerability management, logging, monitoring, and regulatory controls.
Ensure solutions align with approved technology standards, integration patterns, cloud strategies, and target-state architecture.
Collaborate on data models, storage patterns, data quality, lineage, retention, privacy, and performance.
Coordinate with support and operations teams to ensure applications can be monitored, supported, maintained, and recovered.
Follow software-development lifecycle, change-management, security, architecture, data-governance, and release-management standards.
Ensure applications comply with legal, regulatory, privacy, records-management, accessibility, and industry requirements.
Maintain traceability between business requirements, technical designs, code changes, tests, approvals, and releases.
Protect confidential, proprietary, customer, and regulated data throughout the development and production lifecycle.
Ensure artificial-intelligence-generated code and content are reviewed, tested, licensed appropriately, and treated with the same rigor as human-created work.
Contribute reusable engineering patterns, libraries, templates, prompts, skills, development standards, and lessons learned to the broader engineering organization.
Mentor other engineers and help raise the organization’s standards for artificial-intelligence-enabled software delivery.
Desired Qualifications
Experience building artificial-intelligence agents, retrieval-augmented generation solutions, semantic-search applications, document-processing systems, or workflow automation.
Experience with model-evaluation frameworks, prompt testing, artificial-intelligence observability, red-team testing, and responsible-artificial-intelligence 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.
Understanding how mortgage products, servicing operations, borrower experience, compliance, and technology intersect to create business value.
Ability to communicate with mortgage business stakeholders without extensive business translation.
Ability to design 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 artificial-intelligence 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.
Summary:
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.
Essential Job Duties and Responsibilities:
Product and Solution Engineering
Partner directly with business stakeholders to understand operating processes, identify root problems, define measurable outcomes, and engineer effective technical solutions.
Translate ambiguous business needs into clear functional requirements, technical designs, user stories, acceptance criteria, and production-ready software.
Work interactively with users through rapid prototyping, demonstrations, feedback sessions, and iterative releases.
Build new applications and enhance existing platforms across the frontend, backend, application programming interface, integration, data, and infrastructure layers.
Develop intuitive, accessible, responsive, and high-performing user experiences.
Design reusable services, components, APIs, workflows, and integration patterns.
Make thoughtful build-versus-buy and configuration-versus-custom-development recommendations.
Balance delivery speed with security, reliability, maintainability, scalability, and long-term architectural integrity.
AI-Native Engineering
Use modern AI engineering tools throughout the software development lifecycle to improve development speed, quality, testing, documentation, and maintainability.
Design and implement AI-enabled capabilities using large language models, retrieval-augmented generation, embeddings, vector search, structured outputs, tool calling, multimodal models, and agentic workflows.
Build AI agents that can securely interact with applications, APIs, databases, documents, and enterprise systems.
Develop effective prompts, system instructions, context-management strategies, tool definitions, workflows, and reusable AI skills.
Evaluate and select appropriate models based on accuracy, latency, security, cost, reliability, and business requirements.
Implement model evaluations, regression tests, guardrails, human-review controls, grounding, observability, and fallback mechanisms.
Identify and mitigate hallucination, prompt-injection, data-leakage, model-bias, unsafe-output, and unauthorized-tool-use risks.
Measure AI solutions using defined quality, accuracy, safety, performance, adoption, and business-value metrics.
Maintain awareness of rapidly evolving AI models, development tools, frameworks, security risks, and engineering practices.
Software Delivery and Testing
Own software delivery from initial discovery and architecture through development, testing, deployment, production support, and continuous improvement.
Write clean, modular, testable, secure, and well-documented production code.
Develop and maintain unit, integration, API, user-interface, regression, performance, security, and end-to-end automated tests.
Use AI-assisted testing and automation tools while independently validating generated code and test results.
Participate in peer reviews, design reviews, architecture reviews, threat modeling, and release-readiness assessments.
Build and maintain continuous integration and continuous delivery pipelines.
Release software through safe, incremental, observable, and reversible deployment practices.
Ensure that functional requirements and acceptance criteria are demonstrably satisfied before production release.
Application Ownership and Operational Excellence
Serve as the accountable engineer or technical owner for up to three assigned applications.
Maintain a clear understanding of each application’s architecture, business purpose, users, integrations, data flows, dependencies, risks, and operational requirements.
Monitor application availability, performance, capacity, security, errors, and user experience.
Diagnose and resolve production incidents, defects, integration failures, and performance issues.
Perform routine maintenance, framework and dependency upgrades, operating-system or platform updates, certificate renewals, configuration changes, and technical-debt remediation.
Patch application and infrastructure vulnerabilities within established remediation timelines.
Maintain current application documentation, support procedures, runbooks, architecture diagrams, data-flow diagrams, deployment instructions, and recovery procedures.
Participate in incident response, root-cause analysis, corrective-action planning, disaster-recovery testing, and business-continuity exercises.
Recommend modernization, re-platforming, consolidation, or retirement when an application no longer meets business or technical standards.
Security, Architecture, Data, and Support Collaboration
Work closely with the Information Security team to implement secure coding standards, identity and access controls, encryption, secrets management, vulnerability management, logging, monitoring, and regulatory controls.
Partner with Enterprise Architecture to ensure solutions align with approved technology standards, integration patterns, cloud strategies, and target-state architecture.
Collaborate with enterprise database and data-management teams on data models, storage patterns, data quality, lineage, retention, privacy, and performance.
Coordinate with IT Support and operations teams to ensure applications can be effectively monitored, supported, maintained, and recovered.
Work with infrastructure, cloud, network, identity, DevOps, quality-assurance, product, legal, risk, and compliance teams as required.
Clearly communicate technical decisions, constraints, risks, tradeoffs, progress, and recommendations to both technical and nontechnical audiences.
Engineering Standards and Governance
Follow established software-development lifecycle, change-management, security, architecture, data-governance, and release-management standards.
Ensure applications comply with applicable legal, regulatory, privacy, records-management, accessibility, and industry requirements.
Maintain traceability between business requirements, technical designs, code changes, tests, approvals, and releases.
Protect confidential, proprietary, customer, and regulated data throughout the development and production lifecycle.
Ensure AI-generated code and content are reviewed, tested, licensed appropriately, and treated with the same rigor as human-created work.
Contribute reusable engineering patterns, libraries, templates, prompts, skills, development standards, and lessons learned to the broader engineering organization.
Mentor other engineers and help raise the organization’s standards for AI-enabled software delivery.
Other Job Duties and Responsibilities:
Performs other related duties as assigned.
Comply with all company policies and procedures.
Maintain regular and punctual attendance.
Supervisory Responsibilities:
This position is an individual contributor.
Qualifications:
To perform this job successfully, an individual must be able to perform each essential function satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required.
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.
Education and/or Experience:
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.
Certificates, Licenses, Registrations:
None Required
Work Complexity:
Problems and issues faced are general, and may require understanding of broader set of issues but typically are not complex. May require familiarity with the financial/mortgage (or job-specific) industry. Problems require understanding of other job areas. Problems are typically solved through drawing from prior experiences, with analysis of the issue.
Work Environment:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work is normally performed in a typical interior office work environment which does not subject the employee to any hazardous or unpleasant elements. The noise level in the work environment is usually moderate.
Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is frequently required to sit and talk or hear. The employee is occasionally required to stand; walk; use hands to finger, handle, or feel; and reach with hands and arms. The employee must occasionally lift and/or move up to 25 pounds.
Equal Employment Opportunity:
The company is committed to providing equal employment opportunities to all employees and applicants without regard to race, ethnicity, color, sex, marital status, sexual orientation, gender identity or expression, pregnancy, religion, national origin, age (40 and over), disability, military status, genetic information, or any other basis protected by applicable federal, state, or local laws.
Americans with Disabilities Act:
Applicants as well as employees who are or become disabled must be able to satisfactorily perform the essential job functions of the position either with or without reasonable accommodation. Applicants as well as employees are encouraged to meet with Human Resources as the organization shall review reasonable accommodations on a case-by-case basis in accordance with applicable law.
Job Responsibilities:
The statements reflect the general duties and responsibilities considered necessary to perform the essential functions of the job and should not be considered as an all-inclusive list of all the work requirements of the position. The company may change the specific job duties with or without prior notice based on the needs of the organization.