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Credit Acceptance Careers

Subprime auto financing via dealer network

Staff Software Engineer - Consumer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-time$185.8k - $260.1k

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Systems, or a closely related field of study, or equivalent work experience.
  • A minimum of 8 years of software engineering experience or comparable depth of experience.
  • Experience in a lead role overseeing the technical direction of a team of software engineering talent across multiple applications.
  • Expert hands-on experience with Java 17 or 21 and Spring Boot, building and operating production REST and event-driven services, with strong object-oriented design and design-pattern knowledge.
  • Practical experience with modern AI-assisted delivery, including spec-driven development, test automation, continuous integration and continuous delivery 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 such as Amazon EKS, GitOps, identity and access management, secrets management, observability, and reliability practices such as service-level objectives.
  • Hands-on experience designing, building, evaluating, and operating at least one LLM-powered agent in production, including secure tool use such as function calling or 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 the greater Southfield, Michigan area; the greater Bellevue, Washington area; or the San Francisco Bay Area, California.
  • Ability to challenge the status quo and influence stakeholders to create innovative solutions.
  • Ability to collaborate with other team members and seek diverse perspectives to meet business outcomes.
  • Ability to foster strong relationships across the organization.
  • Understanding of relevant and emerging technologies, ability to provide input and coach team members, and ability to embed learning and innovation in day-to-day work.
  • Understanding of how work being done connects to and drives business value.
  • Ability to communicate complex technical information verbally and in writing to all levels, including senior leadership.
  • Sound judgment about where AI should and should not act, including redesigning workflows before automating them, setting clear tool and action boundaries for agents, keeping people involved in customer-impacting decisions, and evaluating AI output for accuracy, safety including prompt injection and data leakage, and bias.
  • Cost- and value-aware engineering, including understanding cloud and AI workload cost drivers such as compute, storage, data transfer, and model tokens, and making evidence-based trade-offs among customer experience, reliability, speed, and spend.
  • Required degrees must have been earned at institutions of higher education accredited by the Council for Higher Education Accreditation or an equivalent accrediting body.

Responsibilities

  • Design, build, and continuously improve cloud-native Java 21 and Spring Boot services on AWS, using AI coding agents as everyday tools while owning the correctness, security, and maintainability of every change.
  • Use spec-driven development by starting each behavior change from a written specification with acceptance criteria and requirement IDs, shipping the specification with the code, and backing it with automated unit, integration, and consumer/provider contract tests such as Pact that block merges when they fail.
  • Lead incremental modernization of Consumer 360 systems by upgrading Java 11 and Spring Boot 2 services to current runtimes, moving ActiveMQ integrations to managed, event-driven messaging, and migrating 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, documentation, and testing standards.
  • Conduct impact analysis to proactively identify the effects of changes across multiple applications.
  • Learn the business process domain to better support the business and align technologies with business processes.
  • Experiment with and test ideas, validate assumptions against needs, reach conclusions, and recommend solutions.
  • Lead code reviews and communicate application changes.
  • Document systems so people and AI agents can build, test, run, and safely change them, including READMEs, agent instruction files such as AGENTS.md, API and event specifications, and short decision records for significant design choices.
  • Debug production problems and propose effective solutions within and across applications.
  • Read, write, and review design documents.
  • Own delivery flow end to end by measuring and shortening requirement-to-production time and removing bottlenecks in specifications, reviews, environments, pipelines, and cross-team dependencies.
  • Lead continuous learning activities to improve design and code quality and increase application domain knowledge.
  • Participate in the talent selection process.
  • Mentor less experienced software engineers by guiding and reviewing their code, designs, and documentation.
  • Design, build, evaluate, and operate production AI agents on AWS, including Amazon Bedrock AgentCore and Spring AI; expose customer context to other teams’ agents through secure, versioned APIs and governed agent tools such as 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 specification through deployment by evolving agentic workflows, maintaining human approval gates, and measuring success by quality and lead time rather than tool usage.
  • Use a customer-empathy approach that understands customer perspectives, pain points, and experiences to support a more customer-centric experience.
  • Apply engineering excellence through craftsmanship, thought leadership, high standards, best practices, innovation, and solutions that meet customer and business needs.
  • Collaborate across the organization with shared goals, open communication, and mutual support.
  • Apply an owner’s mindset through responsibility, accountability, strategic thinking, proactive domain management, deep business and domain understanding, and focus on the right outcomes for the domain and business.
  • Apply an AI-first mindset by starting from AI when building and running software, redesigning work before automating it, using agents to multiply team capacity, and remaining accountable for the quality, security, and cost of AI output.
  • Practice customer data stewardship by protecting personal information, honoring consent and privacy choices, and respecting data ownership and authoritative sources so customers, colleagues, and agents see accurate context.
  • Remain compliant with company policies, processes, and legal guidelines.
  • Perform other duties as assigned.
  • Attend work as required by the department.

Desired Qualifications

  • Advanced use of AI-native development tools such as GitHub Copilot, Claude Code, or similar agents in the IDE and command line, including writing custom instructions, reusable skills and commands, hooks, and MCP integrations that improve team productivity.
  • In-depth creation of APIs and frameworks, including REST/JSON and legacy SOAP web services, JUnit 5 and Mockito, WireMock, consumer-driven contract testing with Pact, and GitHub with GitHub Actions.
  • Experience in API security, analytics, throttling, caching, logging, and request and response modifications.
  • Experience with API-first design, including versioned OpenAPI and event schemas agreed before implementation and published for consumers, people, and agents.
  • 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, including customer master data and identity resolution, consent and privacy-request fulfillment, and sensitive data exchanges such as credit-bureau reporting and disputes, including Metro 2 and e-OSCAR.
  • Experience with AI agent platforms and frameworks such as Amazon Bedrock, Bedrock AgentCore, Spring AI, or LangChain4j; Python agent frameworks are a plus; and experience with LLM evaluation, guardrail, and observability tooling.

About the Company

Credit Acceptance Careers

Subprime auto financing via dealer network

Credit Acceptance provides auto financing solutions for people with poor or no credit by partnering with a network of enrolled car dealers. Dealers in the program can approve loans for customers who are declined by traditional lenders, using a proprietary credit approval process that assesses risk and creditworthiness. The company earns money from interest and fees on these loans, and also offers financial wellness resources like the ExtraCredit program to help customers improve financial literacy. This approach targets the subprime auto market, expanding dealer sales and offering financing options to high-risk borrowers who might otherwise be unable to buy a vehicle. The goal is to help underserved borrowers access auto loans, support dealer networks, and enable customers to rebuild their credit while growing profitability.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Southfield, MI
Founded
1972

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