Senior AI Engineer

- Design, develop, and deploy scalable AI, machine learning and Agentic AI applications for enterprise use cases
- Lead the productionization of AI solutions, transforming PoCs into highly available, resilient, and maintainable production systems
- Build E2E AI pipelines including data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement
- Develop and deploy LLM-powered applications using RAG, AI agents, vector databases, prompt engineering, and model orchestration frameworks
- Design cloud-native AI architectures leveraging containerization, Kubernetes, serverless technologies, and event-driven microservices
- Implement MLOps and AgenticOps best practices, including CI/CD, automated testing, model versioning, observability, drift detection, governance, and rollback strategies
- Optimize AI models for scalability, latency, throughput, reliability, and cost efficiency in production environments
- Collaborate with platform engineering teams to build reusable AI services, APIs, SDKs, and enterprise AI capabilities
- Ensure AI solutions adhere to Mastercard's security, architecture, privacy, compliance, and Responsible AI standards
- Evaluate emerging AI technologies and recommend adoption strategies to accelerate enterprise AI innovation.
- Partner with cross-functional teams to define technical roadmaps and deliver AI capabilities aligned with strategic business objectives