Staff Software Engineer, Consumer 360

Credit Acceptance is proud to be an award-winning company recognized both locally and nationally across multiple workplace categories. Our world-class culture is shaped by dedicated team members who are driven to succeed as professionals individually and together as a team. Backed by a strong product, exceptional people, and a stable financial foundation, we’ve grown into a leading provider of used and new car financing across the country.

This position follows a hybrid work model, offering two work-from-home days and three standard in-office days each week with the team and key stakeholders at the local office.

• 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

• →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

• 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 observability tooling

• Ability to challenge the status quo and influence stakeholders to create innovative solutions
• Be collaborative with other team members, seeking a diversity of thought to meet business outcomes
• Ability to foster strong relationships across the organization
• Bring a strong understanding of relevant and emerging technologies, provide input and coach team members and embed learning and innovation in the day-to-day
• Experience and understanding of how to connect the work being done and how it drives business value
• Ability to communicate complex technical information (both verbal and written) to all levels, including senior leadership
• Sound judgment about where AI should and should not act: redesigns a workflow before automating it, sets clear tool and action boundaries for agents, keeps people in the loop for customer-impacting decisions, and evaluates AI output for accuracy, safety (including prompt injection and data leakage) and bias
• Cost- and value-aware engineering: understands the cost drivers of cloud and AI workloads (compute, storage, data transfer, model tokens) and makes evidence-based trade-offs among customer experience, reliability, speed and spend
• Consumer 360 role-specific behaviors
  • AI-First Mindset: Starts from AI when building and running software. Redesigns the work before automating it, uses agents to multiply the team’s capacity, and stays fully accountable for the quality, security and cost of everything AI produces.
  • Customer Data Stewardship: Treats customer data as a trust obligation. Protects personal information, honors consent and privacy choices, and respects clear data ownership and authoritative sources so customers, colleagues and agents see accurate context.

To be successful in this role, Team Members need to be:

• Positive by maintaining resiliency and focusing on solutions
• Respectful by collaborating and actively listening
• Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions
• Direct by effectively communicating and conveying courage
• Earnest by taking accountability, applying feedback and effectively planning and priority setting

• Remain compliant with our policies processes and legal guidelines
• All other duties as assigned
• Attendance as required by department