Principal Agentic Platforms Architect

In this role you will lead the technical vision and hands-on development of Mastercard’s enterprise agentic AI platforms. You will own the end-to-end architecture for production-grade AI systems at enterprise scale within a security-conscious setting. You will translate complex decisions into clear guidance, mentor engineers, and establish engineering standards to drive security, resilience, and performance. You will collaborate with cross-functional teams to enable secure, multi-tenant, API-first platform capabilities and deliver impactful AI-enabled automation.

• Own enterprise agentic AI platform architecture including runtime environments, orchestration, governance, multi-tenancy, policy enforcement, guardrails, observability, and lifecycle management
• Lead hands-on architecture and development of scalable agentic systems (multi-agent coordination, memory governance, tool calling, Model Context Protocol, human-in-the-loop workflows, autonomous decisions)
• Drive model and platform integration strategy for model-agnostic execution across providers with intelligent routing, cost optimization, and governance controls
• Architect API-first platform capabilities enabling internal teams and external consumers to build, deploy, govern, and operate AI agents via secure interfaces
• Set and enforce technical standards across architecture, code quality, security, resilience, performance, and compliance
• Provide technical direction through architecture and code reviews and act as senior advisor for agentic AI architecture
• Establish architectural governance and documentation including system designs, ADRs, integration specs, and engineering standards
• Mentor engineers and strengthen the organization’s technical capabilities

• 12+ years of hands-on software and AI engineering experience
• Proven experience architecting production-grade agentic AI systems or AI-powered automation
• Deep Python coding skills and experience with modern AI/ML frameworks
• Experience with agentic frameworks such as LangChain, LangGraph, CrewAI or equivalents
• Strong cloud-native architecture experience (AWS, Databricks, Kubernetes)
• Expertise in AI governance, trust, safety, guardrails, policy engines, monitoring, and risk controls
• Experience building enterprise platforms with multi-tenant data architectures, IAM, API-first designs, and data lakehouse patterns
• Ability to communicate complex decisions to executives and stakeholders
• Mentorship and technical leadership track record
• Bachelor’s degree in Computer Science, Engineering, or related field; advanced degree preferred

• Executive-level communication
• Influence and alignment across engineering and business teams
• Resilience and intellectual curiosity
• Python
• AI/ML frameworks
• LangChain