Principal AI Engineer

Mastercard
Singapore
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Problem-solving","Leadership","Communication"]

Senior AI engineering expert leading the design and deployment of advanced agentic AI systems (multi-agent, multi-tool orchestration, memory and retrieval) with a focus on safe tool use, production pipelines, observability, and governance. Partners with platform, security, governance, and product stakeholders to ship measurable business outcomes and raise engineering standards for responsible AI.

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FursaFursa
Mastercard
Mastercard
4 months ago

Principal AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Status: Live

Job Summary

Senior AI engineering expert leading the design and deployment of advanced agentic AI systems (multi-agent, multi-tool orchestration, memory and retrieval) with a focus on safe tool use, production pipelines, observability, and governance. Partners with platform, security, governance, and product stakeholders to ship measurable business outcomes and raise engineering standards for responsible AI.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Serve as an established subject matter expert in AI Engineering, influencing stakeholders and shaping technical direction across multiple initiatives.
  • •Architect, design, develop, and maintain advanced AI/ML systems, with emphasis on complex agentic solutions (multi-agent orchestration, tool/function-calling, memory, reflection/self-correction, and autonomy policies).
  • •Lead production implementation of agentic AI systems, including scalable training and evaluation pipelines, deployment frameworks, and runtime orchestration patterns.
  • •Define and implement safe tool-use patterns: structured outputs, robust error handling, permissioning and auditability, HITL approval steps for sensitive actions, and guardrail enforcement.
  • •Establish end-to-end AgentOps/LLMOps practices for agentic systems: release pipelines for prompts/tools/policies, canary strategies, safe rollback mechanisms, and continuous regression/safety evaluations as release gates.

Key Requirements

  • •Bachelor’s degree in Computer Science, Engineering, Data Science, Applied Mathematics, or related technical field; advanced degree preferred
  • •Strong foundation in software engineering, distributed systems, and applied machine learning relevant to production AI systems
  • •Demonstrated understanding of responsible AI, model/system risk, privacy/security considerations, and governance requirements for enterprise deployments
  • •Demonstrated ownership of production AI/ML systems, including design, build, deployment, and ongoing lifecycle operations
  • •Real-world experience shipping complex agentic systems into production, including multi-agent coordination and multi-tool integration with safe action policies
Experience:AiMachine learningProduction systemsMulti-agent systemsGovernance
Education:Bachelor's in Computer ScienceN/A
Skills:Problem-solvingLeadershipCommunication
Languages:English

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
Glassdoor: 4.1
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