Staff Software Engineer, Consumer 360

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.

Outcomes and Activities:

• •Design, build and continuously improve cloud-native Java 21 / Spring Boot services on AWS, using AI coding agents as everyday tools while owning the correctness, security and maintainability of every change
• •Practice spec-driven development: start each behavior change from a written spec with acceptance criteria and requirement IDs, ship the spec with the code, and back it with automated unit, integration and consumer/provider contract tests (e.g., Pact) that block the merge when they fail
• •Lead incremental modernization of Consumer 360 systems: upgrade Java 11 / Spring Boot 2 services to current runtimes, move ActiveMQ integrations to managed, event-driven messaging, and migrate on-premises workloads and databases to AWS, using facades, side-by-side comparison and safe cutover rather than big-bang rewrites
• •Author, apply and advocate for team coding, documenting and testing standards
• •Conduct impact analysis to proactively identify impact of a change across multiple applications
• •Learn the business process domain to better support the business and align technologies with the business process
• •Experiment and test ideas, validate assumptions against needs, reach conclusions and recommend solutions
• •Lead code reviews and communicate application changes
• •Document systems so both people and AI agents can build, test, run and safely change them: READMEs, agent instruction files (e.g., AGENTS.md), API and event specs, and short decision records for significant design choices
• •Debug the problems which arise in production and propose effective solutions within the application and across multiple applications
• •Read, write and review design documents
• •Own delivery flow end to end: measure and shorten requirement-to-production time by removing bottlenecks in specs, reviews, environments, pipelines and cross-team dependencies
• •Lead continuous learning activities to improve design and code quality as well as to increase application domain knowledge
• •Participate in the talent selection process
• •Act as a mentor to guide and review the code, designs and documentation of less experienced software engineers
• •Design, build, evaluate and operate production AI agents on AWS (Amazon Bedrock AgentCore, Spring AI), and expose customer context to other teams’ agents through secure, versioned APIs and governed agent tools (e.g., MCP), with guardrails, offline and online evaluations, observability, cost controls and human review where customer impact requires it
• •Lead the team’s AI-assisted delivery model from written spec through deployment: evolve its agentic workflows, keep human approval gates, and measure success by quality and lead time rather than tool usage

Competencies: The following items detail how you will be successful in this role.

• •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 8 years of software engineering experience or comparable depth of experience
• •Experience in the lead role overseeing technical direction of a team of software engineering talent across multiple applications
• •Expert, hands-on Java (17/21) and Spring Boot: building and operating production REST and event-driven services, with strong object-oriented design and design patterns
• •Practical experience with modern, AI-assisted delivery: spec-driven development, test automation, CI/CD in GitHub Actions and small, frequent releases
• •Practical experience in data modeling, design and messaging
• •Experience working on mission-critical enterprise class applications
• •Demonstrated ability to coach and mentor less experienced team members
• •Willingness to participate in an on-call rotation
• •Hands-on experience designing, deploying and operating cloud-native services on AWS, including containers on Kubernetes (e.g., Amazon EKS), GitOps, IAM and secrets management, observability and reliability practices such as SLOs
• •Hands-on experience designing, building, evaluating and operating at least one LLM-powered agent in production: secure tool use (e.g., function calling, MCP), retrieval where needed, offline and online evaluation, guardrails, observability and human oversight for consequential actions
• •Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan, area; the greater Bellevue, Washington, area; or the San Francisco Bay Area, California.

Preferred:

• •Advanced use of AI-native development tools (GitHub Copilot, Claude Code or similar agents in the IDE and CLI), including writing custom instructions, reusable skills and commands, hooks and MCP integrations that make the whole team faster
• •In-depth creation of APIs and frameworks: REST/JSON and legacy SOAP web services, JUnit 5 and Mockito, WireMock, consumer-driven contract testing (Pact), and GitHub with GitHub Actions
• •Experience in API security, analytics, throttling, caching, logging, request and response modifications
• •Experience with API-first design: versioned OpenAPI and event schemas agreed before code and published for consumers, people and agents alike
• •Ability to use DDL to create database objects and relationships, construct advanced queries, and optimize query performance
• •Financial services industry experience
• •Experience with customer data in a regulated business: customer master data and identity resolution, consent and privacy-request fulfillment, and sensitive data exchanges such as credit-bureau reporting and disputes (e.g., Metro 2, e-OSCAR)
• •Experience with AI agent platforms and frameworks (Amazon Bedrock and Bedrock AgentCore, Spring AI or LangChain4j; Python agent frameworks a plus) and with LLM evaluation, guardrail and obser