Senior Enterprise Automation & AI Solutions Engineer

Credit Acceptance Corporation

Bellevue (WA)

Hybrid

USD 126,000 - 176,000

Full time

32 hours ago

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Job summary

Credit Acceptance is seeking a seasoned enterprise automation engineer to advance our AI-driven platform. You will configure Jira/Confluence, automate HR/payroll workflows, and partner with product teams to simplify complex processes.

You will lead secure, compliant integrations across enterprise systems, implement governance for AI components, and mentor engineers while delivering measurable productivity improvements in a hybrid Bellevue-based role.

Qualifications

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 SDLC and 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.

Responsibilities

Find friction and simplify before automating. Partner with product owners, service teams, and business stakeholders to prioritize opportunities.
Build and ship productivity solutions. Configure platform workflows, write scripts, expose supported APIs, and use approved low-code tools to automate recurring work.
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.
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.
Evaluate and govern AI before release. Test workflow correctness, response quality, permissions, and failure scenarios before release, and monitor quality and adoption.
Measure productivity outcomes. Establish a baseline with business owners, then measure cycle time, hours released, adoption, and rework.
Operate and release dependable capabilities. Own production reliability for platform capabilities and integrations.
Improve the application portfolio. Maintain inventory, dependencies, license usage, and renewal dates.
Raise engineering quality and enable adoption. Mentor peers, review designs, and establish reusable standards.