Jobs at Credit Acceptance Corporation

Lead development and modernization of cloud-native Java and Spring Boot services on AWS. Drive migration from legacy systems, event-driven architecture, automated testing, documentation, production reliability, and secure API design. Build and operate production AI agents using Amazon Bedrock and related frameworks, with evaluation, guardrails, observability, cost controls, and human oversight. Mentor engineers, lead technical direction and code reviews, improve delivery practices, and collaborate across teams on customer data and enterprise applications.

Owns the production ML and GenAI platform, including training and inference pipelines, model serving, registries, monitoring, evaluations, agent gateways, observability, cost controls, and incident response. The role builds reusable deployment patterns, governs agent tools and access, partners with Cloud Engineering, Data Engineering, Security, and SRE, maintains platform architecture, and mentors engineers. Candidates need strong Python and SQL, production ML operations experience, cloud platform expertise, and familiarity with LLM, agent, and MCP architectures.

Own the technical delivery, automation, integration, security, and reliable operation of workforce applications including ADP, Jira, and Confluence. Build workflow automation and AI-powered self-service using scripting, APIs, low-code tools, and governed agents. Partner with business stakeholders to improve productivity, manage enterprise application portfolios, monitor production services, perform root-cause analysis, and establish secure, reusable engineering standards. Mentor peers and support testing, releases, documentation, adoption, and on-call operations.

Designs, builds, and operates AI-powered ServiceNow self-service and workflow capabilities. The role develops reusable actions, secure integrations, conversational experiences, knowledge retrieval, and automated fulfillment while enforcing access controls, testing, governance, and auditability. Responsibilities include production reliability, monitoring, regression automation, root-cause analysis, release management, outcome measurement, technical leadership, code and design reviews, mentoring, and collaboration with product, business, security, workplace, and enterprise AI teams.

Sets enterprise-wide technical strategy as the senior-most individual contributor in Technology. Owns target architecture, agentic AI foundations, cloud migration to AWS and Databricks, data platforms, model serving, experimentation, marketplace systems, performance, resilience, security, and auditability. The role requires hands-on engineering involvement, including code reviews, proofs of concept, design reviews, and incident analysis, while influencing teams and executives without formal authority and developing staff and principal engineers.

Leads the Platform Services organization, managing teams that build internal developer tooling, shared engineering services, golden-path templates, development environments, and AI-assisted development capabilities. Owns platform strategy, service reliability, security, adoption, productivity measurement, and consolidation of duplicated services. Partners with infrastructure and delivery teams, manages budgets and roadmaps, recruits and develops engineering leaders, and drives organizational change and engineering excellence.

Leads the vision, architecture, strategy, and execution of enterprise data platforms supporting scalable analytics and AI initiatives. Oversees modern data technologies, production reliability, FinOps, governance, architecture standards, and cross-functional delivery. Builds and mentors engineering teams, communicates with executives, evaluates third-party technologies, resolves critical production issues, and drives continuous improvement. The role is remote with occasional planned travel to the Southfield, Michigan office.

Leads and mentors cross-functional engineering teams building and operating distributed, API-driven, cloud-native platforms. Owns technical strategy, architecture, delivery outcomes, engineering excellence, operational reliability, and API lifecycle governance. Drives Agile, DevOps, cloud migration, observability, and incident management practices. Establishes responsible AI adoption across software development and guides delivery of AI-enabled products, including agentic solutions, with appropriate evaluation and controls.

Lead and execute ML/AI strategy, design and deploy production-grade ML and GenAI solutions, mentor MLEs, collaborate with cross-functional teams, and build scalable, secure ML/LLM platforms and inference pipelines to drive business impact.

Owns the technical strategy, roadmap, requirements, and delivery of scalable data solutions. Partners with business, product, design, and engineering teams to prioritize high-impact features, assess vendors, guide architecture, incorporate AI strategies, and resolve technical issues. The role requires strong BI and data warehouse expertise, technical leadership, stakeholder communication, agile product development, customer delivery support, and mentoring responsibilities.

The Senior Data Modeler designs and maintains data models, supports AI-driven practices, and collaborates on data lifecycle processes. Responsibilities include translating business needs into data structures, ensuring data governance, and supporting analytics and AI use cases.

Senior individual contributor owning AI/ML products end-to-end: discover opportunities, define roadmaps, make build-vs-buy decisions, lead vendor evaluations and cross-functional delivery, monitor KPIs and operational signals, and drive continuous improvement and adoption.

Own Sales platforms, data infrastructure, workflows, backlogs, and request intake processes. Translate Sales and GTM needs into technical requirements, user stories, and acceptance criteria while partnering with Product, Analytics, and Engineering through delivery, testing, release, and adoption. Lead cross-functional projects, evaluate systems and integrations, coordinate prioritization, measure utilization and data quality, and recommend scalable improvements. Provide consultative technical support to Sales stakeholders and communicate risks, dependencies, tradeoffs, and delivery status.

Own the lifecycle marketing strategy across email, SMS, push, and in-app channels to increase customer lifetime value. Lead segmentation, onboarding and first-payment journeys, contact strategy, experimentation with holdouts, and performance measurement. Partner with product, creative, operations, analytics, servicing, legal, and compliance teams to deliver compliant customer programs and optimize incremental impact.

Lead complex financial analysis, accounting research, journal entry reviews, reconciliations, variance reporting, internal financial reporting, and control assessments. Provide strategic financial insights to leadership, improve reporting processes, strengthen controls, automate workflows, and manage cross-functional Finance initiatives. Serve as a functional lead by reviewing deliverables, prioritizing workloads, mentoring analysts, and advising business partners on accounting and financial decisions.

Leads the consumer digital experience across website, mobile app, portal, payments, and marketplace surfaces. Owns the multi-year vision, prioritized roadmap, conversion optimization, experimentation, self-service, payment operations, shared digital foundations, and measurable business outcomes. Partners across marketing, engineering, servicing, analytics, and compliance while building and developing product, design, and digital teams.

Leads the consumer acquisition strategy across owned, organic, paid, and emerging channels. Owns growth targets, marketing investment, acquisition contracts, customer acquisition costs, and conversion performance. Directs experimentation, channel optimization, marketplace expansion, seasonal promotions, and innovation initiatives. Partners with digital, creative, dealer marketing, analytics, legal, and compliance teams while building and developing a high-performing acquisition organization.

Lead development and deployment of predictive and ML models for credit risk, collections, and operations. Mentor data scientists, promote MLOps and modern tools, present insights to stakeholders, and drive experimentation with techniques such as causal inference and GenAI.

Leads investor relations strategy, investment-thesis development, earnings communications, investor presentations, and debt capital markets support. Partners with finance, legal, marketing, operations, and executives to ensure accurate external disclosures. Provides market intelligence, investor feedback, valuation insights, and strategic recommendations to leadership while managing relationships with investors, analysts, lenders, and rating agencies. The role also improves reporting and stakeholder engagement through technology, automation, and analytics.

Leads operating expense budgeting, financial planning, variance analysis, spending governance, and executive financial reporting. Partners with senior leaders to evaluate investments, improve resource allocation, and support profitability goals. Manages budget processes and tools while coaching direct reports and providing strategic financial guidance across the business.