Overview

We are seeking an AI Mortgage Operations Solutions Engineer to work directly with Consumer Direct Mortgage Fulfillment and LOS operations leadership to rapidly design, configure, develop, test, and deploy AI-enabled workflow solutions that improve operational efficiency, quality, consistency, visibility, and scalability. This role will operate in a business-embedded model, partnering closely with fulfillment leaders, LOS operations leaders, process owners, operational SMEs, training, risk, compliance, information security, product, and technology teams to identify high-value workflow opportunities and quickly translate them into usable solutions. The ideal candidate combines lending-domain fluency with strong hands-on software engineering skills, an AI-first mindset, workflow automation experience, and the ability to deliver rapid prototypes that can mature into controlled production capabilities.

The role should apply a platform-first delivery approach. The engineer should prioritize approved LOS-native workflow automation, agentic task configuration, permissioning, rules, document handling, integrations, and operational control capabilities before pursuing custom development. Where native capabilities are insufficient, the engineer will design and build lightweight tools, APIs, integrations, dashboards, and utilities that extend the mortgage operations technology ecosystem while remaining aligned with approved architecture, information security, compliance, governance, SDLC, and production support standards.

This role is expected to move quickly, but not casually. The successful candidate must be able to deliver practical solutions with governed speed: rapid delivery inside approved information security, data privacy, architecture, compliance, model governance, auditability, change management, and production support rails.

OPERATING MODEL

This is a business-embedded engineering role. The individual will work closely with Consumer Direct Fulfillment and LOS operations leaders to observe workflow friction, clarify business needs, prototype solutions, validate them with users, and mature successful concepts into production-ready capabilities. The engineer should be comfortable working in a forward-deployed model where requirements may begin as business problems, workflow observations, operational bottlenecks, or SME feedback rather than fully documented specifications.

The role requires strong judgment across multiple solution paths:

• Native platform configuration
• Deterministic workflow automation
• AI-assisted agentic workflow
• Human-in-the-loop review
• Custom software development
• API or event-based integration
• Reporting, dashboarding, or operational monitoring
• Lightweight utilities or internal tools

The engineer should first evaluate whether approved LOS-native workflow and automation capabilities can meet the need. Custom development should be used when native capabilities are unavailable, insufficient, inefficient, or unable to meet user experience, integration, control, scalability, reporting, or supportability requirements.

Responsibilities

• Partner directly with Consumer Direct Mortgage Fulfillment and LOS operations leaders to understand workflows, pain points, capacity constraints, quality issues, exception patterns, manual handoffs, and opportunities for AI-enabled automation.
• Operate in a forward-deployed model, rapidly converting business requirements, process observations, and SME feedback into working prototypes, pilot solutions, and production-ready capabilities.
• Evaluate whether each workflow should be solved through deterministic automation, AI-assisted agentic workflow, human review, custom software development, or a hybrid approach.
• Prioritize approved LOS-native workflow, automation, agentic task, permissioning, rules, document handling, and integration capabilities before building external solutions.
• Design, configure, develop, test, and deploy AI-enabled task flows that combine deterministic automation, AI-assisted interpretation, human review, escalation routing, audit trails, and operational monitoring.
• Define agentic workflow objectives, entry criteria, completion criteria, required evidence, blocking conditions, permission boundaries, escalation paths, human approval points, test cases, rollout criteria, and success measures.
• Configure or support configuration of workflow personas, role-based permissions, document access, loan-data access, integration authorizations, and least-privilege controls where platform-native capabilities are used.
• Translate business requirements into functional solution designs, including workflows, prompts, tools, data inputs, decision logic, user interaction patterns, permission models, audit requirements, and escalation paths.
• Develop custom applications, APIs, workflow utilities, dashboards, integrations, and lightweight services when approved native platform capabilities are not sufficient to meet the business need.
• Integrate AI-enabled solutions with approved enterprise systems, loan origination platforms, document repositories, communication tools, reporting platforms, workflow queues, and third-party services.
• Deliver solutions through approved SDLC practices, including requirements definition, technical design, secure development, peer review, testing, release planning, deployment, documentation, monitoring, and support transition.
• Build solutions that meet enterprise engineering standards for maintainability, security, scalability, observability, reliability, automated testing, version control, and production support.
• Ensure rapid prototypes are evaluated for production readiness before broader deployment, including architecture review, information security review, data access review, model or AI governance review, operational support planning, and rollback or disablement procedures.
• Establish testing protocols for normal cases, negative cases, missing information, conflicting evidence, integration failures, duplicate-order risk, unauthorized-action attempts, human override, and production rollback.
• Design human-in-the-loop review processes, escalation triggers, exception handling, audit evidence, monitoring routines, and governance controls for AI-enabled workflows used in mortgage operations.
• Document solution design, intended use, data sources, business rules, permissions, limitations, testing results, deployment approach, support model, and ongoing monitoring requirements.
• Partner with training and operations leaders to prepare user guidance, adoption plans, feedback loops, measurement plans, and change-management materials.
• Track and communicate value delivered, including cycle-time reduction, productivity improvement, reduced rework, improved consistency, improved operational visibility, reduced manual handoffs, and stronger exception management.
• Use approved enterprise AI, cloud, automation, workflow, and integration platforms as appropriate, while prioritizing native LOS workflow and automation capabilities where they provide the safest, fastest, and most supportable path to value.
• Stay current on emerging AI agent, workflow orchestration, responsible AI, automation, cloud-native, and mortgage operations technology practices.
• Other duties as assigned by leadership.

Qualifications

• 3+ years of experience in software development, automation engineering, AI application development, data engineering, workflow engineering, solutions engineering, or a related technical role.
• Hands-on experience building with large language models, AI agents, copilots, workflow automation, API-based applications, or AI-enabled business process solutions.
• Strong software engineering fundamentals, including modular design, object-oriented or functional programming concepts, API design, data modeling, source control, automated testing, debugging, observability, secure coding, and maintainable code practices.
• Experience delivering software through a structured SDLC, including requirements clarification, design, development, code review, testing, release management, documentation, production deployment, monitoring, incident response, and ongoing support.
• Ability to build production-quality solutions, not just prototypes, with appropriate error handling, logging, configuration management, access control, monitoring, scalability, resiliency, and supportability.
• Experience working directly with business users, operations leaders, or process owners to translate ambiguous operational needs into deployable technical solutions.
• Experience designing workflow-centric solutions involving task routing, exception handling, decision support, user interaction, system integration, and operational monitoring.
• Strong understanding of prompt engineering, retrieval-augmented generation, tool or function calling, structured outputs, agent orchestration, workflow design, and human-in-the-loop patterns.
• Experience integrating applications with APIs, databases, document repositories, workflow platforms, reporting tools, enterprise applications, or business systems.
• Proficiency in one or more programming languages such as Python, JavaScript, TypeScript, C#, Java, or a comparable modern language.
• Ability to evaluate whether a business process should be solved through native platform configuration, workflow automation, AI-assisted reasoning, human review, or custom software development.
• Understanding of role-based access, permission models, least-privilege design, audit trails, escalation workflows, testing controls, and production-readiness requirements.
• Strong problem-solving skills with a bias toward practical delivery, rapid prototyping, iterative feedback, measurable business impact, and production supportability.
• Excellent communication skills, including the ability to work directly with non-technical operations leaders and translate technical concepts into business terms.
• Ability to work effectively in a regulated environment where data privacy, auditability, consistency, borrower impact, quality, compliance, and operational controls are critical.
• Ability to work across approved enterprise platforms and cloud ecosystems without being tied to a single vendor stack.

Preferred Qualifications:

• Experience in mortgage banking, loan origination, consumer direct lending, fulfillment, processing, underwriting support, condition management, closing, servicing, financial services, or another regulated operating environment.
• Familiarity with loan origination systems, lending workflow platforms, document management systems, fulfillment queues, third-party mortgage services, and common mortgage operations workflows.
• Experience in a forward-deployed engineering, solutions engineering, technical product, business automation, operational transformation, or technology consulting role.
• Experience configuring or extending enterprise platforms using native workflow, automation, rules, permissions, integrations, and user-facing configuration capabilities.
• Experience with enterprise AI, cloud, automation, and workflow platforms across one or more major ecosystems, such as AWS, Azure, Google Cloud, OpenAI-compatible services, enterprise low-code/no-code platforms, workflow automation platforms, business intelligence tools, document repositories, collaboration platforms, or similar technologies.
• Experience building AI-enabled applications or workflow automations using cloud-native services, serverless functions, API gateways, event-driven architectures, managed AI services, orchestration tools, or enterprise integration platforms.
• Experience with agentic AI frameworks, orchestration tools, workflow engines, or automation platforms such as Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, AWS Step Functions, Azure Logic Apps, Power Platform, or comparable technologies.
• Experience with retrieval-augmented generation, vector databases, knowledge management systems, document AI, OCR, intelligent document processing, or evidence-backed decision-support workflows.
• Experience deploying AI-enabled prototypes that evolve into governed, monitored, production-supported solutions.
• Familiarity with information security review, model governance, responsible AI practices, data privacy, vendor controls, audit requirements, SDLC controls, and regulatory expectations for financial services technology.
• Experience developing production-ready automations and applications with monitoring, exception handling, logging, retry controls, duplicate-prevention patterns, automated testing, user feedback loops, and rollback procedures.

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