Software Engineering Manager

People & AI-Driven Leadership

The Software Engineering Manager provides hands-on leadership and supervision for a software development team, fostering a culture of continuous learning and adaptation to modern, AI-augmented engineering workflows.

Payment Delivery

Owns end-to-end delivery of FordPay payment capabilities, including credit/debit card processing flows (authorization, capture, settlement, refunds).

PSP Integrations

• Leads integrations and ongoing lifecycle management of Payment Service Providers (PSPs), with Stripe as the primary provider.

Techical Architecture

Facilitates technical architecture discussions around application functionality, payment domain modeling, integration patterns, and the integration of AI capabilities where appropriate.

Transaction Integrity

• Ensures transaction integrity through proven payment engineering patterns (idempotency, deduplication, retries, and safe reconciliation).

AI-Enabled Software Development

Drives the adoption of AI-assisted coding tools (e.g., GitHub Copilot) to accelerate code generation, optimize refactoring, improve code readability, and reduce time-to-market while adhering to secure coding standards.

AI-Enabled Quality Assurance

• Establishes and champions AI-driven testing frameworks and strategies, utilizing intelligent test generation, predictive defect analysis, and automated test-suite optimization to drastically reduce regression cycles and ensure robust coverage.

AIOps

• Evolves the platform’s observability and reliability strategy by leveraging AI/ML-driven monitoring tools for predictive anomaly detection, proactive incident prevention, and automated root-cause analysis (RCA) of payment flows.

Product Partnership

Partners with Product Managers to develop and evolve payment experiences used by Ford customers across eCommerce journeys.

Risk & Compliance Mitigation

• Actively identifies risks (e.g., PSP dependency, latency, fraud/chargeback exposure, compliance gaps) and implements mitigation and contingency plans, ensuring AI-generated code and tools comply with security (PCI DSS) and IP guidelines.

Metrics & Telemetry

Verifies that delivered software meets desired business outcomes (payment success rates, reliability, customer experience, and operational readiness) using both traditional telemetry and AI-driven predictive insights.

Incident Management

• Reviews ongoing production operations; leads incident response and post-incident reviews (postmortems/RCAs) to prevent recurrence, utilizing AI-assisted diagnostics to speed up resolution times.

Safety & Compliance

• Ensures secure payment design and compliance posture in partnership with Security/Compliance teams (e.g., PCI DSS controls, secure token handling).

Agile Practices

Actively participates in all team Agile ceremonies and champions Agile software processes, culture, best practices, and techniques.

Talent Development

Develops engineering, professional, and career-related skills for engineers through coaching, mentorship, feedback, and collaborative practices—specifically preparing the workforce for the future of AI-augmented engineering.

Qualifications

• Bachelor's degree in information technology or computer science, or similar discipline.
• 10+ years of experience in a Software Engineering role with people leadership experience (engineering management).
• Experience leading engineering teams in adopting and optimizing AI-assisted software development tools (e.g., GitHub Copilot, Gemini Code Assist, or similar AI coding assistants) to drive developer velocity and code quality.
• Hands-on understanding or experience with AI-driven QA automation, predictive testing tools, and modern AI-powered testing methodologies.
• Strong knowledge of Java, JavaScript, React, Spring Boot, and building API-first microservices.
• Experience building cloud-native solutions (Google Cloud Platform preferred) and operating high-availability systems.
• Experience working with DevOps/Security tools like GitHub, Cloud Build, Tekton, 42Crunch, FOSSA, SonarQube, Cycode, etc.
• Strong leadership and communication skills and the ability to coach, teach, and guide teams through technological paradigm shifts (such as the integration of AI in software engineering).