Top Tech Jobs & Startup Jobs

Lead design, build, and operate scalable data pipelines and data products to support foundation model training, inference, and evaluation. Partner with AI and platform teams to enable feature engineering, ensure data quality, governance, lineage, and secure access. Drive best practices for modeling, partitioning, performance, monitoring, and CI/CD. Provide technical leadership, code/design reviews, mentoring, and program-level planning to ensure production-ready, reliable data for AI workloads.

Supports cybersecurity issue and control management across Mastercard’s technology environment. Responsibilities include triaging and validating security issues in Archer, reviewing risk statements and control mappings, evaluating remediation plans and evidence, assessing compensating controls, tracking risk treatment, supporting control assessments, and producing governance reporting. The role partners with engineering, risk, compliance, and governance stakeholders to drive remediation or risk acceptance and maintain audit-defensible documentation.

Leads and develops a high-performing software engineering team building full-stack business experimentation and optimization applications. Responsibilities include supervising and mentoring engineers, designing scalable service-oriented architectures, leading projects from inception through release, developing software, reviewing code, planning features, improving engineering processes, and collaborating across teams. The role requires expertise in full-stack, data, cloud, microservices, databases, and advanced software development practices.

Leads hands-on development of backend and full-stack capabilities for Mastercard’s real-time Decision Management Platform. Responsibilities include designing scalable services, APIs, workflow tools, integrations, and user experiences; making architecture decisions; writing and reviewing code; mentoring engineers; and supporting testing, deployment, observability, security, and production operations. The role requires translating ambiguous business goals into reliable software and measurable outcomes.

Lead technical direction and hands-on development for Mastercard’s enterprise Developer Workbench platform. Design platform components, developer tooling, onboarding environments, AI-assisted development capabilities, and cloud-native integrations. Establish tooling governance, instrumentation, security and compliance practices, and developer productivity metrics. Partner cross-functionally with product and engineering teams, mentor engineers, influence architecture, and advance software engineering standards across the organization.

Lead design, build, and operate scalable, governed data pipelines and products for foundation models and AI workloads. Partner with AI and platform teams to enable feature engineering, training/inference datasets, data quality, lineage, and secure access. Provide technical leadership, code/design reviews, mentoring, and delivery planning across cloud-native distributed data environments.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Own ingestion, transformation, streaming and batch patterns, feature engineering support, data quality, lineage, governance, and performance optimization. Collaborate with AI, platform, and product teams, lead technical reviews, mentor engineers, and contribute to program planning and delivery oversight.

Manages Mastercard payment resiliency products focused on stand-in and on-demand authorization decisioning. Acts as a regional subject-matter expert, partners with sales, account management, consulting, customer success, and engineering teams, and drives product adoption and performance. Develops business cases, analyzes market and customer data, identifies product opportunities and risks, supports product enhancements, and communicates strategic recommendations to stakeholders. Requires strong leadership, analytical, communication, and stakeholder-management skills, plus payments or authorization decisioning familiarity.

Lead design, build, and operate scalable data pipelines and data products to support foundation models and AI workloads. Own ingestion, transformation, feature engineering, governance, quality checks, monitoring, and collaboration with AI, platform, and product teams. Mentor engineers and drive delivery, standards, and secure, production-ready datasets for training, inference, and evaluation.

Supports North American sales of Mastercard Identity solutions by serving as the technical product expert. Responsibilities include discovery, solution design, technical presentations, proof-of-value testing, customer training, documentation, conferences, webinars, and product feedback. The role requires explaining machine learning, data science, APIs, web architecture, and probability-based decisioning to technical and nontechnical stakeholders while advising customers on fraud and identity solutions.