Top Tech Jobs & Startup Jobs

Lead advanced quantitative analysis of primary market research using methods such as Conjoint, MaxDiff, segmentation, and regression. Design experiments, validate models, interpret results, advise on methodology, partner with cross-functional teams, mentor junior analysts, and help build analytics standards and tools to support multi-market consulting engagements.

Lead design and deliver production-grade agentic AI applications and cloud-native services. Define engineering patterns, ensure security, observability, and reliability, drive SDLC improvements, mentor engineers, collaborate with AI, product, and platform teams, and move prototypes to governed production.

Manage end-to-end sales lifecycle support for Mastercard Services: coordinate deal structuring, CRM governance, pricing approvals, contracting, billing transitions, and process improvements to ensure accurate deal execution, revenue realization, and stakeholder alignment across Sales, Finance, Legal, and Delivery.

Lead hands-on design and delivery of secure, scalable agentic AI applications and platform capabilities. Drive architecture, implementation, SDLC, observability, security, and cross-functional collaboration to take AI solutions from prototype to governed production. Mentor engineers and shape roadmaps to enable reliable, maintainable, and high-impact product delivery.

Lead strategy, architecture, and delivery of Mastercard's data platform for analytics and agentic AI. Design lakehouse, streaming, retrieval, vector/feature stores, and MCP servers. Ensure governance, lineage, observability, and AI-specific controls. Partner with Applied AI, Product, and Security; guide and grow a senior data engineering team while remaining hands-on to unblock technical challenges.

Design, provision, and operate high-volume, low-latency decisioning infrastructure across public and private clouds. Build and optimize CI/CD pipelines, implement Infrastructure as Code, drive observability and reliability, and collaborate with global engineering teams to support, troubleshoot, and scale the real-time Decision Management Platform.

Lead and scale Quality Engineering across full-stack and data/ML products. Define QE strategy, drive test automation, shift-left/right practices, establish AI/ML and data quality frameworks, own release quality gates, investigate production incidents, manage budget/vendor relationships, and hire and develop global QE teams to ensure product reliability and customer experience.

Lead and scale a global Quality Engineering function across full-stack and data/ML systems. Define QE strategy, drive test automation, shift-left/right practices, establish AI and data quality frameworks, own release gates, perform RCA on incidents, manage budget and vendors, and recruit and develop QE leadership.

Design, provision, and operate high-volume, low-latency decisioning infrastructure across public and private clouds. Build CI/CD pipelines, implement IaC, enable observability, optimize cost, and collaborate with global engineering teams to support real-time fraud, risk, and identity decision systems.

Lead design and deliver production-ready agentic AI applications and platform capabilities. Define engineering patterns, drive end-to-end SDLC, mentor engineers, ensure security, observability, reliability, cost controls, and collaborate with Product, Applied AI, Data Science, and stakeholders to move AI solutions from prototype to governed production.