Principal AI Engineer Job at Mastercard (Singapore)

Principal AI Engineer

Mastercard

Location:
Singapore , Singapore

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

As a Principal AI Engineer on the AI Foundations team, you are an established subject matter expert in AI Engineering who applies expert knowledge and experience to drive achievement of key area goals and initiatives by making significant improvements to new or existing products, services, and/or processes. You lead the design and operationalization of complex, production-grade agentic systems—particularly multi-agent, multi-tool solutions that plan, call tools safely, maintain memory, and continuously improve through evaluation and feedback. You influence technical direction across programs, set engineering standards for reliability and responsible AI, and partner with platform, security, governance, and product stakeholders to ship measurable business outcomes.

Job Responsibility:

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, human-in-the-loop (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
Build and optimize data ingestion, preprocessing, feature/embedding engineering, and retrieval/memory workflows to improve grounding quality and reduce failure modes
Own production observability for agentic systems: trace capture, cost/token telemetry, latency and reliability SLOs, and incident response practices for agent failures
Implement drift detection and performance decay monitoring (data drift, concept drift), and automate model/agent retraining, policy updates, and redeployment to maintain output quality over time
Drive measurable improvements in system effectiveness, safety, and efficiency by defining success metrics (task success, intervention rate, policy violations, cost and latency per task) and continuously improving evaluation coverage
Mentor and grow senior and junior engineers through design reviews, code reviews, hands-on coaching, and the creation of reusable patterns, playbooks, and standards for agentic delivery

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, sustained 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
Hands-on experience building production pipelines for evaluation, monitoring, versioning, and continuous improvement (including retraining or policy/guardrail updates)
Proven ability to define and operationalize observability and reliability practices for agentic systems (traceability, telemetry, SLOs, incident management)
Track record of influencing architecture and standards across multiple teams or programs, and mentoring engineers to raise overall engineering rigor

Additional Information:

Job Posted:
April 16, 2026

Employment Type:

Fulltime

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