Senior Workforce Solutions Engineer

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

• •Find friction and simplify before automating. Partner with product owners, service teams, and business stakeholders to prioritize opportunities. Eliminate unnecessary steps and favor platform-native capabilities over customization.
• •Build and ship productivity solutions. Configure platform workflows, write scripts, expose supported APIs, and use approved low-code tools to automate recurring work. Deliver production solutions with clear ownership and support.
• •Engineer AI-powered self-service. Engineer conversational experiences, knowledge, workflows, and agent capabilities, applying deterministic automation where appropriate and bounded AI reasoning where it adds value.
• •Create reusable, trustworthy capabilities. Build documented actions, integrations, and templates that serve multiple teams, favoring supported native capabilities over one-off custom solutions. Connect portfolio applications with enterprise systems using supported APIs and secure data exchange, with validation, monitoring, retries, and exception handling.
• •Engineer trusted enterprise context for AI. Improve knowledge quality with content owners and implement permissions-aware retrieval grounded in authoritative information.
• •Protect access and sensitive data. Configure least-privilege roles, integration identities, and secrets management. Support access reviews and audit evidence with application owners and Security, preserving segregation of duties, especially for HR and payroll processes.
• •Evaluate and govern AI before release. Test workflow correctness, response quality, permissions, and failure scenarios before release, and monitor quality and adoption in production without exposing sensitive data in logs or test datasets. Build in human approval for sensitive actions, audit trails, and the ability to suspend faulty automation.
• •Measure productivity outcomes. Establish a baseline with business owners, then measure cycle time, hours released, adoption, and rework. Distinguish capacity released from realized savings.
• •Operate and release dependable capabilities. Own production reliability for platform capabilities and integrations. Use logs, alerts, and root-cause analysis to reduce recurring failures. Monitor task completion, self-service resolution, and latency. Automate regression testing, maintain source control, and document runbooks. Participate in the on-call rotation.
• •Improve the application portfolio. Maintain application inventory, dependencies, license usage, and renewal dates. Recommend consolidation or retirement based on usage, cost, and business value, coordinating with owners, Finance, Procurement, and vendors.
• •Raise engineering quality and enable adoption. Mentor peers, review technical designs, and establish reusable standards for testing, integrations, and AI-enabled workflows. Use approved AI tools in engineering and review generated output. Evaluate emerging AI capabilities and recommend roadmap improvements based on business value. Provide user guidance and knowledge transfer.

Requirements

• •Bachelor's degree in Computer Science, Information Systems, or a closely related field, or equivalent work experience.
• •6+ years of experience administering and engineering enterprise business applications, with a demonstrated record of shipping automation and improving business workflows.
• •Hands-on Atlassian administration and automation experience, including Jira and Confluence, plus ADP or a comparable payroll or HR platform.
• •Scripting and integration experience using Python, PL/SQL, JavaScript, REST APIs, or webhooks, including supporting integrations in production.
• •Practical experience applying generative AI or agent tools to business workflows, including evaluation, data access controls, and human oversight.
• •Experience building secure, compliant applications, including access controls and sensitive data handling for HR, payroll, and financial processes; familiarity with standards such as SOC 2.
• •Experience with incident resolution, root-cause analysis, and technical documentation for enterprise applications.
• •Practical expertise in the Software Development Life Cycle (SDLC) and Agent Development Life Cycle (ADLC), including Agile/SCRUM practices, testing, release management and DevOps practices.
• •Experience providing technical leadership and mentoring to other engineers.
• •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

• •Atlassian or ADP certifications.
• •Experience with enterprise low-code automation, knowledge and search quality, approved AI assistants, or reusable agent tools and actions.
• •Experience exposing enterprise actions to external AI agents through governed APIs or standards such as Model Context Protocol (MCP), and with AI evaluation datasets.
• •Experience with license optimization, application consolidation, and integrating workforce applications with ServiceNow, identity, or collaboration platforms.

Knowledge and Skills

• •Problem Solving: Diagnose and debug complex systems.
• •Learning Agility: Learn and engineer across a varied application portfolio.
• •Business Partnership: Clarify problems, explain tradeoffs, and deliver usable solutions with measurable outcomes.
• •Communication: Explain complex technical information, verbally and in writing, to all levels, including senior leadership.
• •Influence and Leadership: Mentor engineers, challenge the status quo, and influence stakeholders toward innovative solutions.
• •Emerging Technology: Understand AI, agentic systems, and automation, and embed continuous learning and experimentation into day-to-day engineering.

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