Mastercard

1 month ago

Director, Software Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Lead and accelerate the engineering delivery of agentic AI platforms at Mastercard, building scalable, secure production systems where intelligent agents serve as personas and orchestrated digital workers. Drive architecture, tooling, and governance while partnering with Applied AI, Data Science, Security, Risk, and Platform teams to turn experiments into enterprise-ready solutions that scale across products and teams.

Location: Mexico City

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Director level

Key Responsibilities

•Define and lead the engineering vision for agentic applications, agent frameworks, and reusable AI platform capabilities that can be adopted across multiple products and teams.
•Build and scale engineering teams that create agents as product capabilities, agent personas for targeted workflows, and orchestration layers that support multi-step reasoning, tool use, and action execution.
•Drive the architecture and delivery of production-grade agentic systems, including context management, memory, tool integration, workflow orchestration, observability, evaluation, and safety guardrails.
•Establish a common agentic engineering framework that standardizes how teams design, build, test, deploy, monitor, and improve intelligent agents at enterprise scale.
•Partner with Product, Data Science, Security, Risk, and Platform teams to identify high-value use cases and translate them into scalable software solutions.

Key Requirements

•Bachelor’s degree in computer science, Software Engineering, or a related technical field; advanced degree preferred.
•15+ years of experience leading software engineering organizations, including managers and multiple cross-functional teams, in product, platform, or enterprise technology environments.
•Strong track record of building scalable, secure, resilient distributed systems and cloud-native platforms used across multiple teams or business domains.
•Hands-on experience building or scaling Generative AI, LLM-powered applications, AI agents, workflow automation, or adjacent intelligent software systems.
•Deep understanding of agentic engineering concepts such as tool calling, orchestration, planning, memory, context handling, retrieval, evaluation, observability, and human-in-the-loop controls.

Experience:15+ yearsPaymentsFintechFinancial services

Education:Bachelor's

Skills:LeadershipCommunicationStakeholder managementProblem-solving

Languages:English

Tech Stack:AWSAzureKubernetesCloud-nativeLLMGenerative AIObservabilityTool callingWorkflow orchestration

Company Brief

Mastercard

Mastercard is a global payments and technology company that processes transactions, provides fraud prevention and data services, and builds payment infrastructure for consumers, businesses, merchants and governments across 200+ countries.

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Mastercard

1 month ago

Director, Software Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Mexico City

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Director level

Key Responsibilities

•Define and lead the engineering vision for agentic applications, agent frameworks, and reusable AI platform capabilities that can be adopted across multiple products and teams.
•Build and scale engineering teams that create agents as product capabilities, agent personas for targeted workflows, and orchestration layers that support multi-step reasoning, tool use, and action execution.
•Drive the architecture and delivery of production-grade agentic systems, including context management, memory, tool integration, workflow orchestration, observability, evaluation, and safety guardrails.
•Establish a common agentic engineering framework that standardizes how teams design, build, test, deploy, monitor, and improve intelligent agents at enterprise scale.
•Partner with Product, Data Science, Security, Risk, and Platform teams to identify high-value use cases and translate them into scalable software solutions.

Key Requirements

•Bachelor’s degree in computer science, Software Engineering, or a related technical field; advanced degree preferred.
•15+ years of experience leading software engineering organizations, including managers and multiple cross-functional teams, in product, platform, or enterprise technology environments.
•Strong track record of building scalable, secure, resilient distributed systems and cloud-native platforms used across multiple teams or business domains.
•Hands-on experience building or scaling Generative AI, LLM-powered applications, AI agents, workflow automation, or adjacent intelligent software systems.
•Deep understanding of agentic engineering concepts such as tool calling, orchestration, planning, memory, context handling, retrieval, evaluation, observability, and human-in-the-loop controls.

Experience:15+ yearsPaymentsFintechFinancial services

Education:Bachelor's

Skills:LeadershipCommunicationStakeholder managementProblem-solving

Languages:English

Tech Stack:AWSAzureKubernetesCloud-nativeLLMGenerative AIObservabilityTool callingWorkflow orchestration

Company Brief

Mastercard

Industry: Payments

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Purchase, New York, United States

Founded: 1966

Glassdoor: 4.1

Website LinkedIn Glassdoor