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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # VP/D Enterprise Decision Engineering - **Company:** OneMain - **Location:** Baltimore, MD, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Ibm Odm, Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Confluence, JIRA, Automation of Tests, Microsoft Azure, Business Process Model and Notation, Continuous Integration, Information Engineering, Drools, Java Platform Enterprise Edition (J2EE), Github, JSON, Java Business Process Management, Apache Maven, OpenShift, Scrum Methodology, Site Reliability Engineering Practices, Cloud Services, Prometheus, Rule Engine, Systems Integration, Extensible Markup Language (XML), Grafana, Spring-boot, Mttr, Kubernetes, Information Technology, Interactive Whiteboards, Restful APIs, Data Pipelines, Docker, Jenkins, Data Generation - **Published:** May 15, 2026 - **Apply:** https://jobs.onemainfinancial.com/job/baltimore/vp-d-enterprise-decision-engineering/21631/95087400720 ## About the Role * 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. ## Description What makes a VP/D Enterprise Decision Engineering successful at OneMain? Check out the top traits we're looking for and see if you qualify. * Adaptable * Analytical * Curious * Entrepreneurial * Inventive * Problem Solver Culture * We foster an entrepreneurial spirit that's powered by a national brand - our teams are empowered to make a difference * We encourage teams to take ownership of initiatives in this fast-paced, innovative culture so they can drive solutions that stay ahead of customer needs * We prioritize teamwork and building in-person connections with each other, understanding that fostering a collaborative environment is the best way to support each other. * We promote avenues to allow team members to expand their professional capabilities and continuously develop skills, facilitating upward mobility and career progression I like working at OneMain because of the opportunity it provides. You get to work with a lot of talented people, a lot of motivation to better the lives of our customers and a lot of fun technology that you get to interact with on a daily basis. I feel like I have many different options that I can take on yearly., 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., 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. ## Related Videos - [Next Level Enterprise Architecture: Modular, Flexible, Scalable, Multichannel and AI-Ready?](https://www.wearedevelopers.com/videos/1017-next-level-enterprise-architecture-modular-flexible-scalable-multichannel-and-ai-ready) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [What Developers Get Wrong About Application Quality](https://www.wearedevelopers.com/videos/233-what-developers-get-wrong-about-application-quality) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)