Job Title:

Software Engineer II

Overview:

Our Vision — AI Data Engineering AI Data Engineering (AIDE) will be the backbone that transforms approved AI ideas into secure, scalable, and reliable production capabilities across Mastercard. We will engineer trustworthy data foundations, streamline model development and fine‑tuning, and operate a frictionless path to deployment and continuous improvement—so every internal process, product, and service can harness AI at scale to advance our customer value, experience, and efficiency.

Opportunity Join Mastercard's AIDE @ Gurgaon/Pune/Vadodara, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The professional will be responsible for the creative application and execution of AI/ML use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate.

Role • Serve as a data engineering (and MLOps) subject matter expert at Mastercard, responsible for end-to-end ownership of data pipelines, model deployment, and productionization of approved AI solutions. • Design and maintain robust, scalable, and secure data architectures ensuring compliance with Mastercard’s standards for data governance, privacy, and regulatory requirements across ingestion, storage, access, and retention. • Translate complex technical requirements into clear, actionable solutions that align with business objectives and stakeholder needs. • Collaborate with global teams to understand business problems, ensuring data and infrastructure readiness for AI/ML initiatives. • Build and optimize data pipelines, feature stores, and model serving frameworks to enable efficient training, fine-tuning, and continuous improvement of AI models. • Implement CI/CD workflows for data and models, including automated testing, monitoring, and rollback strategies to ensure reliability and resilience in production environments. • Identify opportunities for reusable components and standardized templates, enabling a microservice approach to scaling AI solutions across Mastercard. • Leverage open-source and enterprise-grade technologies for data engineering, orchestration, and deployment to deliver high-performance solutions. • Work cross-functionally with data scientists, architects, and product teams to operationalize AI models and integrate them seamlessly into Mastercard’s ecosystem. • Champion a learning and innovation culture, continuously advancing AIDE capabilities and best practices for data engineering.

All About You

Experience • Proven ability to deliver production-grade AI data engineering solutions in complex, matrix environments. • 6+ years in data engineering/MLOps, building pipelines and deploying models at scale. • Core expertise: • Java (primary) for high-performance services and microservices. • Kubernetes for container orchestration, Helm, autoscaling, secure deployments. • Cloudera (CML/CDE) for Spark/HDFS workloads and governance. • Apache NiFi for secure, auditable data flows. • Strong skills in data pipelines, feature stores, Spark, Kafka, Hive, SQL, and model lifecycle (packaging, serving, monitoring, rollback). • Hands-on with CI/CD, infra-as-code, observability, and enterprise security (RBAC, PKI, compliance logging). • Familiarity with Python for ML workflows; partner effectively with data scientists. • Experience with collaboration tools (Confluence, Bitbucket) and SAFe or similar frameworks. • Knowledge of payments industry and regulatory context is a plus.

Effectiveness • Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum • Capable of navigating a complex organization in a relentless pursuit of answers and clarity • Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness • Proven thought-leadership when evaluating business problems and architecting a cohesive solution • Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation • Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment • Incredible attention to detail and focus instilling confidence without qualification in developed solutions

Core Capabilities • Strong written and oral communication skills • Bachelor's degree required. Advanced degree in Management, Mathematics, Computer Science, Engineering, or other quantitative fields desirable

To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.