Top Tech Jobs & Startup Jobs

Leads hands-on development of secure, scalable AI and agentic platform capabilities. Designs and delivers reusable services, APIs, integrations, workflows, data pipelines, knowledge-base extensions, and orchestration layers. Provides technical direction, reviews code, mentors engineers, coordinates vendors, and translates architecture into production solutions. Partners across product, business, data, and engineering teams while ensuring reliability, security, privacy, compliance, cost efficiency, and operational readiness.

Supports Mastercard’s shared-services operational risk management program by identifying and assessing risks, evaluating control gaps, coordinating remediation, maintaining risk registers and reporting, conducting incident root-cause analysis, and supporting audits, compliance monitoring, SOX, technology risk, and enterprise risk activities. The role also develops key risk indicators, process documentation, presentations, and AI-based preventative and detective controls.

Leads hands-on development of AI and agentic platform capabilities, including LLM integrations, orchestration, workflows, APIs, data pipelines, and knowledge bases. Translates architecture and product priorities into secure, scalable solutions; guides engineers and vendors; conducts design and code reviews; mentors team members; and ensures reliability, privacy, security, compliance, and production readiness.

Leads hands-on development of AI and agentic systems for a scalable enterprise AI platform. Designs and delivers reusable services, integrations, workflows, APIs, data pipelines, knowledge-base capabilities, and orchestration layers. Provides technical direction, reviews code, mentors engineers and vendors, and partners across product, business, architecture, and engineering teams. Ensures production solutions meet security, privacy, compliance, reliability, scalability, and cost objectives.

Leads enterprise platform architecture across hybrid and cloud infrastructure, AI platforms, security, compliance, modernization, and sustainability initiatives. Defines target-state architectures, reference patterns, and roadmaps; drives automation and platform simplification; partners with security and technology teams; manages budgets and multiple teams; mentors architects and engineers; and influences executive technology strategy.

Supports Mastercard’s product and solution commercialization by researching markets, analyzing client and competitive needs, developing business cases, preparing RFPs and executive presentations, and contributing to solution positioning and growth strategies. Collaborates across business units and manages multiple workstreams while delivering clear business insights, recommendations, and client-facing materials.

Develop and maintain secure, scalable backend services, RESTful APIs, and integrations supporting internal platforms, data products, and customer applications. Collaborate with product, architecture, data engineering, and data science teams; participate in design, testing, code reviews, CI/CD, monitoring, and production support. Troubleshoot issues, perform root cause analysis, improve reliability, and follow security, privacy, and compliance standards.

Leads hands-on development of secure, scalable AI and agentic platform capabilities. Designs and integrates LLM services, agent frameworks, workflow engines, knowledge bases, APIs, data pipelines, and orchestration layers. Translates architecture and product priorities into production solutions, guides engineers and vendors, reviews code, manages technical risks, and supports migration to future-state platforms. Partners across product, data, business, architecture, and engineering teams while ensuring reliability, security, privacy, compliance, and operational readiness.

Lead hands-on development of secure, scalable AI and agentic platform capabilities. Design and integrate LLMs, AI services, agent frameworks, workflow engines, knowledge bases, APIs, data pipelines, and orchestration layers. Translate architecture and product priorities into production-ready solutions, provide technical direction, review code, mentor engineers, coordinate vendors, and ensure reliability, security, privacy, compliance, and scalability. Support AI platform migration, reusable engineering patterns, FinOps, TokenOps, and commercialization of AI-enabled consulting solutions.

Lead hands-on development of AI and agentic systems for Mastercard’s consulting-focused AI platform. Responsibilities include designing scalable services, APIs, workflows, data pipelines, integrations, and knowledge-base capabilities; integrating LLMs and orchestration platforms; guiding engineers and vendors; conducting design and code reviews; supporting migrations; and ensuring security, privacy, compliance, reliability, and scalability. The role requires strong software engineering, distributed systems, cloud and data platform experience, technical leadership, mentoring, and expertise in production-grade AI solutions.