• Drive technical strategy for model integration, enabling:

  • Model-agnostic agent execution
  • Cost optimization, routing intelligence, and governance controls at platform level

• Architect API-first interfaces that empowers:

  • Internal teams and external consumers to build, deploy, govern, and operate AI agents
  • Using programmatic, language-agnostic access patterns

• Define and enforce engineering standards including:

  • High security, resilience, performance, and compliance requirements

• Provide deep leadership on:

  • Agentic AI design patterns (e.g., retrieval-augmented generation, tool calling via Model Context Protocol, multi-step orchestration, human-in-loop workflows)

• Act as a technical advisor to senior leadership, translating complex decisions into clear business-relevant language.

• Mentor and develop a high-performing engineering team, fostering:

  • Technical excellence, intellectual honesty, and continuous improvement
  • A culture of rigorous code review and transparency.

• Produce and maintain architectural documentation, including:

  • System design documents
  • Architecture decision records (ADRs)
  • Integration specifications

Requirements & Qualifications

Experience & Background

• 15+ years of hands-on software and AI engineering experience, with a significant portion focused on production-grade AI systems
• Proven track record in designing, building, and deploying agentic AI, multi-agent platforms, or AI-powered automation in production (real users, real data, real consequences not just proofs of concept)
• Deep coding proficiency—write production code, review production code, and hold others to the same standard (not a diagram-drawing role)
• Advanced expertise in Python and modern AI/ML frameworks, with hands-on experience in agentic toolkits such as LangChain, LangGraph, or CrewAI

Technical Expertise

• Cloud-native platforms: Strong experience designing for scalability, resilience, and high availability on AWS, Databricks, and Kubernetes
• AI governance & safety: Deep understanding of guardrails, policy engines, behavioral analytics, red teaming, and compliance strategies
• Multi-tenant platforms: Ability to design platforms with access control and enterprise-grade identity management
• API-first architectures: Experience designing RESTful and SDK interfaces for both internal and external consumers
• Data architectures: Experience with Delta Lake, vector databases, and retrieval-augmented generation (RAG) systems
• Model integration: Experience with model-agnostic tool call protocols and integration over multiple LLM providers

Soft Skills & Leadership

• Exceptional communication: Ability to explain technical concepts to both non-technical stakeholders and development teams
• Known for building trust, mentoring others, and setting high standards—focused on excellence over titles
• Bring intellectual curiosity, resilience, and energy to solving hard problems

Education

• Bachelor’s in Computer Science, Engineering, or related field (Advanced degree is preferred but not mandatory if experience is demonstrated)

Corporate Security Responsibility

All activities involving Mastercard assets, information, or networks carry organizational risk. It is expected that all employees:

1. Abide by Mastercard’s security policies and practices
2. Ensure confidentiality and integrity of information
3. Report any suspected security breaches or violations immediately
4. Complete mandatory security trainings as required

Note: The role prioritises experience over rigid criteria—exceptional candidates with comparable experience will be considered if they have demonstrated equivalent expertise.