Advance your potential – and reach your goals

As OneMain expands its market verticals, a multi-product strategy is evolving to penetrate markets through compelling customer engagement. Correspondingly, teams deliver products across a variety of platforms and technologies. Our products and platforms span AWS, Azure, IBM iSeries and zSeries, and OpenShift on-prem as part of a hybrid strategy. With both disparate technology delivery and varying regulatory requirements, OneMain’s environment is both complex and evolving, supporting a broadening multi-product, multi-market strategy.

We’re seeking a senior, hands-on engineering leader to build and scale an Enterprise Decision Engineering organization and lead the transformation of OneMain’s credit & pricing decisioning from mainframe to a cloud-native Decision Platform (Drools/Kogito & Decision Intelligence). Build a Decision Solutions CoE and deliver Decisioning-as-a-Service so product teams can safely author, test, and deploy decision logic - faster, with auditability and measurable business impact. This leader will own delivery, quality, and operational excellence for decisioning that powers credit, pricing, and risk strategies across consumer lending.

The person in this role should have proven success leading cross-functional credit/lending programs into production at scale with an in-depth understanding of business-rules engines (ODM, FICO Blaze, Drools/Kogito), Java/cloud engineering.The VP/D Enterprise Decision Engineering will be an integral member of Data Engineering and Operations leadership team, lead a team of 20+ engineers and will be reporting to Head of Credit & Pricing Technology. This role will provide strategic leadership and tactical execution of the Enterprise Decisioning platform management function.

RESPONSIBILITIES:

What you will own

• Strategy & Transformation: Lead the migration of Credit & Pricing decisioning from iSeries/zSeries mainframes to a modern Decision Platform (Drools/Kogito, Decision Intelligence), including a Next-Gen Offer service platform for pricing. Define roadmap, sequencing, risk mitigation, and business value capture.
• Drive program execution: sprint planning alignment, roadmap tradeoffs, cross-team orchestration, and stakeholder communications to senior leadership.
• Delivery & Quality: Own end-to-end execution from requirements to release for decisioning services - ensuring high velocity, near-zero high-severity defects, and strong reliability SLAs.
• Release governance: Approve production rule releases and pricing changes; enforce go/no-go criteria and rollback plans.
• Lead architectural reviews and standardization: Drive standardization for data contracts, service APIs and cloud deployment patterns (Kubernetes/OpenShift).
• Sponsor automation & Gen AI initiatives: Synthetic data pipelines, regression suites and CI/CD for rule deployments & GenAI enablement for rule authoring and test scenario validations.
• Ensure strong observability: Using OpenTelemetry, Prometheus, Grafana, alerting, SRE practices and on-call readiness for decision services.
• Define and track engineering KPIs (velocity, deployment frequency, MTTR, defect trends & performance).
• Drive compliance activities: model governance, validation evidence, audit-ready documentation and legal sign-offs for pricing & credit changes.
• Business Partnership: Partner with Product, Credit, Pricing, Fraud, Compliance and Legal to align on risk tolerances, policy, regulatory filings, and financial assumptions; represent engineering in executive forums.
• People & Capability: Recruit, coach and scale engineering teams to transitioning to modern stacks. Create upskilling programs (rule engine, cloud, observability, GenAI for rules).
• Security & Compliance: Ensure decisioning satisfies data privacy, auditability, explainability, and regulatory requirements (consumer disclosure, state filings).

Key deliverables & Success Criteria

• Drive program execution: sprint planning alignment, roadmap tradeoffs, cross-team orchestration, and stakeholder communications to senior leadership.
• Own release governance for decisioning: Approve production releases and pricing changes; enforce go/no-go criteria and rollback plans.
• A production-grade Decision Platform running core credit and pricing decision logic, with a migration plan and measurable progress against mainframe retirement targets.
• Next-Gen Offer Service for pricing written on Drools, integrated via REST APIs, with parity tests and performance SLAs.
• Decision Solutions COE with documented rule lifecycle governance, reusable components (authoring, simulation, testing), and Decisioning-as-a-Service onboarding playbooks.
• Measurable improvements in engineering KPIs: release frequency, on-time delivery reduced high-priority incidents, and decreased rule deployment time.
• Production observability, regression suites, automated rollback and incident playbooks implemented across decisioning services.
• Upskilled mainframe teams transitioned into new roles and capabilities in Drools/Java/cloud delivery.

QUALIFICATIONS:

• Leadership: 10+ years building and scaling engineering organizations for credit/financial systems; experience managing managers and multi-disciplinary teams.
• Business Rules & Decisioning: Deep, hands-on experience with rule engines and decision platforms (IBM ODM, FICO Blaze Advisor, Drools/Kogito, BPMN/JBPM), rule lifecycle & governance.
• Credit & Lending Domain: Strong knowledge of lending products, underwriting logic, scorecards, PD/LGD, vintage analytics, regulatory/disclosure requirements, collections, and pricing strategy.
• Modern Engineering: Java / J2EE, Spring Boot, REST APIs, Maven; cloud deployments (AWS preferred, Azure acceptable), Kubernetes/OpenShift, Docker.
• Data & Formats: XML, JSON, integrations to core data stores/feeds, real-time orchestration.
• Observability & Automation: OpenTelemetry, Prometheus, Grafana, Jenkins or GitHub Actions, CI/CD, regression suites, synthetic data generation and test automation.
• Tools & Agile: Jira, Confluence, Miro; experience leading Agile at scale and governance for multi-team delivery.
• BA/BS Degree in computer science or engineering is preferred, MS degree is desirable or equivalent professional experience as a substitute for either degree
• DBA certifications are preferred.
• Azure or AWS Cloud Certifications are preferred.