American Express
American Express
American Express is a global financial services company operating across banking, finance, and B2B payments. Its business includes consumer, business, and corporate credit cards; payment and merchant services; savings accounts, certificates of deposit, and personal loans; as well as rewards, travel programs, corporate payment solutions, financial education, security services, and cardmember and merchant support.

Director of Software Engineering, Data Platforms and Generative AI – American Express Hybrid India

Lead American Express’s modernization of servicing data platforms, metadata management, DaaS, MaaS, and Generative AI foundations. Build enterprise-scale engineering teams and reusable intelligence capabilities.

Description

  • Own the strategy, roadmap, and delivery of servicing data platforms spanning DaaS, MaaS, operational data engineering, reporting, customer journey intelligence, data ingestion, and data lake modernization
  • Develop and deliver multi-year cloud-first strategies for AI-enabled platform modernization
  • Improve platform simplicity, standardization, reuse, scalability, resilience, availability, performance, and operational excellence
  • Lead teams responsible for platform engineering, reliability, automation, and lifecycle management
  • Develop trusted, accessible, reusable, and consumable servicing data capabilities
  • Define enterprise approaches for data federation, metadata, lineage, cataloging, context propagation, and reusable intelligence services
  • Provide real-time and near-real-time access to servicing data through governed APIs, event-driven architectures, and intelligence access layers
  • Expand DaaS and MaaS adoption across business and technology teams
  • Integrate governance, privacy, security, compliance, data quality, retention, auditability, and access controls into platforms and engineering practices
  • Lead reusable intelligence components and foundational services for AI, analytics, automation, customer intelligence, predictive analytics, Generative AI, agentic systems, and decisioning
  • Assess emerging AI and data technologies and establish strategies for enterprise adoption
  • Own the servicing operational reporting ecosystem, advancing self-service reporting, standardized metrics, real-time intelligence, and reusable reporting frameworks
  • Build and develop a high-performing engineering organization through coaching, mentoring, succession planning, and technical leadership development
  • Define engineering operating models, delivery practices, quality standards, and cross-functional partnerships

Requirements

  • Bachelor’s degree in computer science, computer engineering, information systems, or a related technical field; an advanced degree is preferred
  • At least 10 years of progressive software engineering and technology experience, including substantial leadership of large engineering teams and enterprise platforms
  • Track record of leading enterprise data platform engineering organizations with accountability for strategy, architecture, execution, reliability, and operational excellence
  • Advanced experience designing, building, and modernizing cloud-native data platforms, distributed systems, data lakes, and large-scale ecosystems for mission-critical capabilities
  • Success delivering multi-year platform modernization and cloud transformation programs focused on simplicity, standardization, scalability, resilience, automation, and reuse
  • Strong experience with Data as a Service, Metrics as a Service, reusable data products, intelligence access layers, ingestion platforms, and governed APIs
  • Deep knowledge of data ingestion and processing, federation, metadata, quality, lineage, cataloging, master data management, and enterprise data lifecycles
  • Strong understanding of real-time and near-real-time architectures, event-driven systems, streaming, APIs, distributed processing, and operational reporting platforms
  • Experience delivering enterprise operational reporting and analytics, standardized metrics and KPIs, self-service analytics, real-time intelligence, and reusable reporting frameworks
  • Experience establishing AI-ready data foundations for advanced analytics, machine learning, Generative AI, customer intelligence, agentic systems, automation, and intelligent decisioning
  • Strong knowledge of modern AI/ML and Generative AI ecosystems, including LLMs, RAG, vector databases, semantic search, knowledge management, context engineering, and reusable intelligence services
  • Ability to assess emerging data, cloud, AI, and Generative AI technologies and create enterprise adoption strategies
  • Strong understanding of enterprise data governance, security, privacy, risk, and regulatory obligations
  • Ability to establish engineering standards and operating models that improve quality, delivery speed, availability, resilience, performance, observability, and operational effectiveness
  • Ability to collaborate across Product, Technology, Data Science, Enterprise Architecture, Information Security, Risk, Compliance, Operations, and business teams
  • Strong business and technology judgment
  • Exceptional communication and ability to influence executives
  • Demonstrated people leadership in building, developing, mentoring, and scaling high-performing engineering organizations
  • Ability to lead through influence in complex, matrixed organizations
  • Strong commitment to engineering excellence and continuous improvement

Benefits

  • Competitive base pay
  • Bonus opportunities
  • Programs supporting financial well-being and retirement
  • Comprehensive medical, dental, vision, life insurance, and disability coverage, subject to location
  • Flexible work arrangements, including hybrid, onsite, or virtual options based on the role and business needs
  • Generous paid parental leave, subject to location
  • Complimentary access to global onsite wellness centers staffed by nurses and doctors, subject to location
  • Free, confidential counseling through the Healthy Minds program
  • Career development and training programs

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