Lead AI Platform Engineer
$168k - $277k • New York City, New York • Full-time
Posted 3d ago
Job Location
New York City, New York
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Infrastructure Engineer
About the job
Mastercard is seeking a Lead AI Platform Engineer to provide technical leadership in designing, implementing, and operating foundational platforms for AI and machine learning workloads. This role operates at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations, focusing on delivering scalable, secure, and reliable AI infrastructure. You will help shape the platforms, tooling, and operational practices for the next generation of AI capabilities, addressing complex challenges in scalability, reliability, observability, governance, and automation. The ideal candidate combines advanced software engineering and cloud platform expertise with experience supporting production AI/ML systems, and is passionate about technical leadership, automation, and building empowering platforms.
Responsibilities
- Lead the design, development, and operation of enterprise platforms for machine learning, generative AI, agentic AI, and advanced analytics.
- Translate business, engineering, and operational requirements into scalable platform solutions.
- Design and maintain advanced AI/ML systems meeting enterprise requirements for security, reliability, availability, scalability, and performance.
- Own technical delivery across public and private cloud environments, resolving complex challenges and influencing cross-functional decisions.
- Build and optimize services and workflows for AI solution onboarding, development, deployment, operations, and lifecycle management.
- Develop infrastructure, tooling, and services for model training, evaluation, fine-tuning, deployment, inference, monitoring, and governance.
- Lead the implementation of scalable and secure MLOps capabilities and AI development workflows.
- Build and optimize data ingestion, preprocessing, and feature engineering workflows.
- Design observability capabilities including telemetry, performance monitoring, logging, alerting, and model monitoring.
- Ensure operational stability and scalability of AI platforms, driving improvements in reliability, resilience, efficiency, security, and customer experience.
- Lead troubleshooting, root cause analysis, and incident response for complex platform issues.
- Influence platform architecture through design discussions, reviews, prototypes, and technical recommendations.
- Partner with engineering and product teams to understand requirements and guide solution design.
- Collaborate with infrastructure, security, architecture, risk, and governance teams to align capabilities with enterprise standards.
- Evaluate emerging AI technologies and industry trends to recommend improvements to Mastercard's AI ecosystem.
- Drive engineering best practices across Infrastructure as Code, CI/CD, automated testing, secure development, and documentation.
- Guide and mentor engineers through design guidance, technical reviews, and problem-solving support.
Requirements
- Experience designing, building, and operating cloud-native platforms or large-scale distributed systems in enterprise environments.
- Strong experience delivering solutions across public and private cloud environments.
- Experience deploying and managing containerized workloads.