Senior AI Engineer
Mastercard20 hours ago
Pune, IndiaSenior
Responsibilities
- Design, develop, deploy, and operate scalable AI, machine learning, generative AI, and agentic AI applications.
- Productionize AI proofs of concept into highly available, resilient, and maintainable enterprise systems.
- Build end-to-end pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement.
- Develop LLM-powered applications using RAG, vector databases, prompt engineering, AI agents, and model orchestration frameworks.
- Design cloud-native architectures using containerization, Kubernetes, serverless technologies, and event-driven services.
- Implement MLOps and AgenticOps practices including automated deployment, model versioning, observability, drift detection, governance, and rollback strategies.
- Optimize models and AI services for scalability, latency, throughput, reliability, and cost efficiency.
- Build reusable AI services, APIs, SDKs, and enterprise AI capabilities with platform engineering teams.
- Ensure solutions meet security, privacy, compliance, architecture, and Responsible AI standards.
- Evaluate emerging AI technologies and help define technical roadmaps aligned with business objectives.
Requirements
- Bachelor's or master's degree in computer science, artificial intelligence, software engineering, or a related field.
- Extensive experience building and deploying production AI/ML systems in enterprise environments.
- Strong software engineering skills with Python, Java, or similar programming languages.
- Experience developing cloud-native applications on AWS, Azure, or Google Cloud Platform.
- Hands-on experience with Docker, Kubernetes, and other containerization or orchestration technologies.
- Strong understanding of distributed systems, APIs, microservices, and event-driven architectures.
- Experience implementing CI/CD pipelines and MLOps frameworks for automated model deployment and lifecycle management.
- Experience with PyTorch, TensorFlow, Scikit-learn, LangChain, LangGraph, LlamaIndex, or equivalent AI frameworks.
- Experience deploying LLMs, RAG solutions, vector databases, and AI agent frameworks.
- Knowledge of model monitoring, observability, performance optimization, AI governance, and Responsible AI practices.
- Strong communication and stakeholder management skills with the ability to influence technical decisions.
Tech Stack
Categories
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).