Credit Acceptance Corporation
San Francisco, California
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
defi AUTO LLC
Jefferson City, Missouri
Job Description Job Description About defi SOLUTIONS: It's an exciting time to join defi! defi SOLUTIONS is a pioneer in end-to-end, SaaS loan originations, servicing, and managed servicing solutions. Our customers include the highest-volume captive auto lenders, banks, credit unions, and finance companies in North America. We have more than three decades of experience helping lenders reduce time-to-market, streamline operations, and customize lending processes with proven, scalable performance. Learn more at and follow us on LinkedIn. About the Role: defi SOLUTIONS builds loan origination and servicing software for banks, credit unions and lenders. We are hiring Senior Software Engineers to build and evolve our auto, mortgage and banking platform across .NET services, Vue.js front ends, SQL Server data, and the cloud infrastructure that runs them. This role exists because we are expanding AI-assisted development across our engineering teams. You will use AI coding tools and agents every day, help shape how we use them, and be accountable for what they produce. We want engineers with sharp analytical skills who can break ambiguous features into well-scoped work, review generated code critically, and ship secure, tested software for regulated financial institutions. Essential Job Responsibilities: Design, build and maintain features across our .NET services, Vue.js UI, and SQL Server schema (versioned through Flyway migrations). Break features and epics into well-scoped, independently deliverable tasks with clear acceptance criteria. Work with AI coding assistants and agents to accelerate delivery, and critically review all AI-generated code for correctness, security, performance and maintainability before it ships. Apply the testing pyramid: unit, integration and end-to-end tests that give fast, reliable feedback. Apply proven design patterns and secure-coding practices to code that handles sensitive lending data. Diagnose and resolve complex production and performance issues, using logs, traces and metrics to find root cause. Containerize and deploy services using Docker, Kubernetes, Helm and Terraform on Azure or AWS. Build and improve CI/CD pipelines, and contribute to agentic tooling (MCP servers, hooks, custom skills) that makes the team faster and safer. Partner with product, QA and client-facing teams to translate lending business rules into reliable software. Required Qualifications: 5+ years of professional software development experience, including significant time building and operating production systems. Domain and judgment Working knowledge of the auto, mortgage or banking domain (origination, underwriting, decisioning, servicing, or related compliance). Strong analytical and problem-solving skills, with a track record of debugging hard, ambiguous issues to root cause. Ability to break features into well-scoped tasks and estimate and sequence them. Engineering fundamentals Strong command of design patterns and when not to use them. Practical experience with the testing pyramid and writing maintainable automated tests. Working knowledge of OWASP Top 10 and secure development practices. AI-assisted development Hands-on experience with agentic development using LLM-based coding tools. Demonstrated ability to critically review AI-generated code: catching subtle bugs, insecure patterns, unnecessary complexity and hallucinated APIs. Technology Stack Area Required Preferred Back end .NET (C#) Front end Vue.js / Razor Data SQL Server Cloud Azure or AWS Infrastructure as code Terraform Containers and orchestration Docker, Kubernetes, Helm VM-based infrastructure Delivery CI/CD pipelines Observability OpenTelemetry (OTEL Preferred Qualifications: Experience building agentic tooling: MCP servers, hooks and custom skills. Hands-on CI/CD pipeline design in Azure DevOps or a comparable platform. Experience with containers and virtual machines in production, including OpenTelemetry-based tracing and metrics. Experience in regulated environments (SOC 2, FFIEC) serving financial institutions. Affirmative Action/EEO statement: defi SOLUTIONS is an Equal Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status.
Job Description Job Description About defi SOLUTIONS: It's an exciting time to join defi! defi SOLUTIONS is a pioneer in end-to-end, SaaS loan originations, servicing, and managed servicing solutions. Our customers include the highest-volume captive auto lenders, banks, credit unions, and finance companies in North America. We have more than three decades of experience helping lenders reduce time-to-market, streamline operations, and customize lending processes with proven, scalable performance. Learn more at and follow us on LinkedIn. About the Role: defi SOLUTIONS builds loan origination and servicing software for banks, credit unions and lenders. We are hiring Senior Software Engineers to build and evolve our auto, mortgage and banking platform across .NET services, Vue.js front ends, SQL Server data, and the cloud infrastructure that runs them. This role exists because we are expanding AI-assisted development across our engineering teams. You will use AI coding tools and agents every day, help shape how we use them, and be accountable for what they produce. We want engineers with sharp analytical skills who can break ambiguous features into well-scoped work, review generated code critically, and ship secure, tested software for regulated financial institutions. Essential Job Responsibilities: Design, build and maintain features across our .NET services, Vue.js UI, and SQL Server schema (versioned through Flyway migrations). Break features and epics into well-scoped, independently deliverable tasks with clear acceptance criteria. Work with AI coding assistants and agents to accelerate delivery, and critically review all AI-generated code for correctness, security, performance and maintainability before it ships. Apply the testing pyramid: unit, integration and end-to-end tests that give fast, reliable feedback. Apply proven design patterns and secure-coding practices to code that handles sensitive lending data. Diagnose and resolve complex production and performance issues, using logs, traces and metrics to find root cause. Containerize and deploy services using Docker, Kubernetes, Helm and Terraform on Azure or AWS. Build and improve CI/CD pipelines, and contribute to agentic tooling (MCP servers, hooks, custom skills) that makes the team faster and safer. Partner with product, QA and client-facing teams to translate lending business rules into reliable software. Required Qualifications: 5+ years of professional software development experience, including significant time building and operating production systems. Domain and judgment Working knowledge of the auto, mortgage or banking domain (origination, underwriting, decisioning, servicing, or related compliance). Strong analytical and problem-solving skills, with a track record of debugging hard, ambiguous issues to root cause. Ability to break features into well-scoped tasks and estimate and sequence them. Engineering fundamentals Strong command of design patterns and when not to use them. Practical experience with the testing pyramid and writing maintainable automated tests. Working knowledge of OWASP Top 10 and secure development practices. AI-assisted development Hands-on experience with agentic development using LLM-based coding tools. Demonstrated ability to critically review AI-generated code: catching subtle bugs, insecure patterns, unnecessary complexity and hallucinated APIs. Technology Stack Area Required Preferred Back end .NET (C#) Front end Vue.js / Razor Data SQL Server Cloud Azure or AWS Infrastructure as code Terraform Containers and orchestration Docker, Kubernetes, Helm VM-based infrastructure Delivery CI/CD pipelines Observability OpenTelemetry (OTEL Preferred Qualifications: Experience building agentic tooling: MCP servers, hooks and custom skills. Hands-on CI/CD pipeline design in Azure DevOps or a comparable platform. Experience with containers and virtual machines in production, including OpenTelemetry-based tracing and metrics. Experience in regulated environments (SOC 2, FFIEC) serving financial institutions. Affirmative Action/EEO statement: defi SOLUTIONS is an Equal Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status.
defi AUTO LLC
Carson City, Nevada
Job Description Job Description About defi SOLUTIONS: It's an exciting time to join defi! defi SOLUTIONS is a pioneer in end-to-end, SaaS loan originations, servicing, and managed servicing solutions. Our customers include the highest-volume captive auto lenders, banks, credit unions, and finance companies in North America. We have more than three decades of experience helping lenders reduce time-to-market, streamline operations, and customize lending processes with proven, scalable performance. Learn more at and follow us on LinkedIn. About the Role: defi SOLUTIONS builds loan origination and servicing software for banks, credit unions and lenders. We are hiring Senior Software Engineers to build and evolve our auto, mortgage and banking platform across .NET services, Vue.js front ends, SQL Server data, and the cloud infrastructure that runs them. This role exists because we are expanding AI-assisted development across our engineering teams. You will use AI coding tools and agents every day, help shape how we use them, and be accountable for what they produce. We want engineers with sharp analytical skills who can break ambiguous features into well-scoped work, review generated code critically, and ship secure, tested software for regulated financial institutions. Essential Job Responsibilities: Design, build and maintain features across our .NET services, Vue.js UI, and SQL Server schema (versioned through Flyway migrations). Break features and epics into well-scoped, independently deliverable tasks with clear acceptance criteria. Work with AI coding assistants and agents to accelerate delivery, and critically review all AI-generated code for correctness, security, performance and maintainability before it ships. Apply the testing pyramid: unit, integration and end-to-end tests that give fast, reliable feedback. Apply proven design patterns and secure-coding practices to code that handles sensitive lending data. Diagnose and resolve complex production and performance issues, using logs, traces and metrics to find root cause. Containerize and deploy services using Docker, Kubernetes, Helm and Terraform on Azure or AWS. Build and improve CI/CD pipelines, and contribute to agentic tooling (MCP servers, hooks, custom skills) that makes the team faster and safer. Partner with product, QA and client-facing teams to translate lending business rules into reliable software. Required Qualifications: 5+ years of professional software development experience, including significant time building and operating production systems. Domain and judgment Working knowledge of the auto, mortgage or banking domain (origination, underwriting, decisioning, servicing, or related compliance). Strong analytical and problem-solving skills, with a track record of debugging hard, ambiguous issues to root cause. Ability to break features into well-scoped tasks and estimate and sequence them. Engineering fundamentals Strong command of design patterns and when not to use them. Practical experience with the testing pyramid and writing maintainable automated tests. Working knowledge of OWASP Top 10 and secure development practices. AI-assisted development Hands-on experience with agentic development using LLM-based coding tools. Demonstrated ability to critically review AI-generated code: catching subtle bugs, insecure patterns, unnecessary complexity and hallucinated APIs. Technology Stack Area Required Preferred Back end .NET (C#) Front end Vue.js / Razor Data SQL Server Cloud Azure or AWS Infrastructure as code Terraform Containers and orchestration Docker, Kubernetes, Helm VM-based infrastructure Delivery CI/CD pipelines Observability OpenTelemetry (OTEL Preferred Qualifications: Experience building agentic tooling: MCP servers, hooks and custom skills. Hands-on CI/CD pipeline design in Azure DevOps or a comparable platform. Experience with containers and virtual machines in production, including OpenTelemetry-based tracing and metrics. Experience in regulated environments (SOC 2, FFIEC) serving financial institutions. Affirmative Action/EEO statement: defi SOLUTIONS is an Equal Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status.
Job Description Job Description About defi SOLUTIONS: It's an exciting time to join defi! defi SOLUTIONS is a pioneer in end-to-end, SaaS loan originations, servicing, and managed servicing solutions. Our customers include the highest-volume captive auto lenders, banks, credit unions, and finance companies in North America. We have more than three decades of experience helping lenders reduce time-to-market, streamline operations, and customize lending processes with proven, scalable performance. Learn more at and follow us on LinkedIn. About the Role: defi SOLUTIONS builds loan origination and servicing software for banks, credit unions and lenders. We are hiring Senior Software Engineers to build and evolve our auto, mortgage and banking platform across .NET services, Vue.js front ends, SQL Server data, and the cloud infrastructure that runs them. This role exists because we are expanding AI-assisted development across our engineering teams. You will use AI coding tools and agents every day, help shape how we use them, and be accountable for what they produce. We want engineers with sharp analytical skills who can break ambiguous features into well-scoped work, review generated code critically, and ship secure, tested software for regulated financial institutions. Essential Job Responsibilities: Design, build and maintain features across our .NET services, Vue.js UI, and SQL Server schema (versioned through Flyway migrations). Break features and epics into well-scoped, independently deliverable tasks with clear acceptance criteria. Work with AI coding assistants and agents to accelerate delivery, and critically review all AI-generated code for correctness, security, performance and maintainability before it ships. Apply the testing pyramid: unit, integration and end-to-end tests that give fast, reliable feedback. Apply proven design patterns and secure-coding practices to code that handles sensitive lending data. Diagnose and resolve complex production and performance issues, using logs, traces and metrics to find root cause. Containerize and deploy services using Docker, Kubernetes, Helm and Terraform on Azure or AWS. Build and improve CI/CD pipelines, and contribute to agentic tooling (MCP servers, hooks, custom skills) that makes the team faster and safer. Partner with product, QA and client-facing teams to translate lending business rules into reliable software. Required Qualifications: 5+ years of professional software development experience, including significant time building and operating production systems. Domain and judgment Working knowledge of the auto, mortgage or banking domain (origination, underwriting, decisioning, servicing, or related compliance). Strong analytical and problem-solving skills, with a track record of debugging hard, ambiguous issues to root cause. Ability to break features into well-scoped tasks and estimate and sequence them. Engineering fundamentals Strong command of design patterns and when not to use them. Practical experience with the testing pyramid and writing maintainable automated tests. Working knowledge of OWASP Top 10 and secure development practices. AI-assisted development Hands-on experience with agentic development using LLM-based coding tools. Demonstrated ability to critically review AI-generated code: catching subtle bugs, insecure patterns, unnecessary complexity and hallucinated APIs. Technology Stack Area Required Preferred Back end .NET (C#) Front end Vue.js / Razor Data SQL Server Cloud Azure or AWS Infrastructure as code Terraform Containers and orchestration Docker, Kubernetes, Helm VM-based infrastructure Delivery CI/CD pipelines Observability OpenTelemetry (OTEL Preferred Qualifications: Experience building agentic tooling: MCP servers, hooks and custom skills. Hands-on CI/CD pipeline design in Azure DevOps or a comparable platform. Experience with containers and virtual machines in production, including OpenTelemetry-based tracing and metrics. Experience in regulated environments (SOC 2, FFIEC) serving financial institutions. Affirmative Action/EEO statement: defi SOLUTIONS is an Equal Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status.