Leads the architecture, development, deployment, and lifecycle management of enterprise AI, machine learning, generative AI, and agentic AI platforms. Establishes AI engineering standards, MLOps and AgenticOps practices, cloud-native architectures, governance, security, and operational excellence. Partners with architecture, security, product, data science, and infrastructure teams to define roadmaps, evaluates emerging technologies, mentors engineers, and drives production adoption of scalable AI capabilities.
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead AI Engineer
Overview
As a Lead AI Engineer within Mastercard's AI Center of Excellence, you will provide technical leadership for the design, architecture, and delivery of enterprise AI and Agentic AI solutions that support Mastercard's strategic initiatives. You will lead multidisciplinary engineering teams in building scalable, secure, and production-ready AI platforms and applications while driving engineering excellence, innovation, and adoption of AI across the organization
You will own the technical vision for AI engineering initiatives, establish enterprise standards and best practices, and collaborate closely with product, architecture, security, infrastructure, and business stakeholders to deliver high-impact AI capabilities at scale
Key Responsibilities
- Lead the architecture, design, and implementation of enterprise AI, machine learning, and Generative AI platforms and applications
- Drive the E2E delivery of production AI solutions, from solution architecture and engineering through deployment, monitoring, optimization, and lifecycle management
- Define enterprise AI engineering standards, reference architectures, reusable frameworks, and best practices for scalable AI development
- Lead the design and implementation of cloud-native AI platforms leveraging microservices, Kubernetes, APIs, event-driven architectures, and distributed systems
- Establish and evolve MLOps and AgenticOps capabilities, including automated CI/CD pipelines, model governance, observability, evaluation, security, and operational excellence
- Architect and deliver advanced Generative AI solutions LLMs, RAG, AI agents, vector databases, prompt engineering, and model orchestration frameworks
- Ensure AI systems meet enterprise requirements for scalability, resilience, security, compliance, Responsible AI, and operational reliability
- Partner with Enterprise Architecture, Platform Engineering, Data Science, Product Management, and Security teams to define AI technology roadmaps and implementation strategies
- Evaluate emerging AI technologies and drive innovation through proofs of concept, technology assessments, and enterprise adoption strategies
- Provide technical leadership and mentorship to AI engineers, fostering engineering excellence, knowledge sharing, and continuous improvement
- Lead technical design reviews, architecture governance, and engineering decision-making across AI initiatives
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering or a related field
- Extensive experience designing, developing, and deploying enterprise-scale AI and machine learning solutions in production
- Demonstrated experience leading technical teams and delivering complex software engineering initiatives.
- Strong expertise in software engineering using Python
- Deep experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, including cloud-native architecture and services
- Strong knowledge of distributed systems, microservices, APIs, containerization, Kubernetes, and infrastructure automation
- Proven experience implementing enterprise MLOps and AgenticOps practices, including model deployment, monitoring, governance, and continuous delivery
- Hands-on experience with modern AI frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, LangGraph, LlamaIndex, or equivalent technologies
- Experience architecting and deploying Agentic AI applications using LLMs, RAG, vector databases, AI agents, and model evaluation frameworks
- Strong understanding of AI governance, Responsible AI, security, privacy, and regulatory compliance
- Excellent communication, stakeholder management, and technical leadership skills
What You'll Deliver
- Enterprise AI platforms and applications that enable secure, scalable, and reusable AI capabilities across Mastercard
- Technical leadership that accelerates the adoption of AI while maintaining engineering quality, operational excellence, and governance
- Modern AI engineering practices that improve developer productivity, deployment velocity, and production reliability
- Strategic AI solutions that drive business innovation, operational efficiency, and customer value across the enterprise
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Lead AI Engineer
Overview
As a Lead AI Engineer within Mastercard's AI Center of Excellence, you will provide technical leadership for the design, architecture, and delivery of enterprise AI and Agentic AI solutions that support Mastercard's strategic initiatives. You will lead multidisciplinary engineering teams in building scalable, secure, and production-ready AI platforms and applications while driving engineering excellence, innovation, and adoption of AI across the organization
You will own the technical vision for AI engineering initiatives, establish enterprise standards and best practices, and collaborate closely with product, architecture, security, infrastructure, and business stakeholders to deliver high-impact AI capabilities at scale
Key Responsibilities
- Lead the architecture, design, and implementation of enterprise AI, machine learning, and Generative AI platforms and applications
- Drive the E2E delivery of production AI solutions, from solution architecture and engineering through deployment, monitoring, optimization, and lifecycle management
- Define enterprise AI engineering standards, reference architectures, reusable frameworks, and best practices for scalable AI development
- Lead the design and implementation of cloud-native AI platforms leveraging microservices, Kubernetes, APIs, event-driven architectures, and distributed systems
- Establish and evolve MLOps and AgenticOps capabilities, including automated CI/CD pipelines, model governance, observability, evaluation, security, and operational excellence
- Architect and deliver advanced Generative AI solutions LLMs, RAG, AI agents, vector databases, prompt engineering, and model orchestration frameworks
- Ensure AI systems meet enterprise requirements for scalability, resilience, security, compliance, Responsible AI, and operational reliability
- Partner with Enterprise Architecture, Platform Engineering, Data Science, Product Management, and Security teams to define AI technology roadmaps and implementation strategies
- Evaluate emerging AI technologies and drive innovation through proofs of concept, technology assessments, and enterprise adoption strategies
- Provide technical leadership and mentorship to AI engineers, fostering engineering excellence, knowledge sharing, and continuous improvement
- Lead technical design reviews, architecture governance, and engineering decision-making across AI initiatives
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering or a related field
- Extensive experience designing, developing, and deploying enterprise-scale AI and machine learning solutions in production
- Demonstrated experience leading technical teams and delivering complex software engineering initiatives.
- Strong expertise in software engineering using Python
- Deep experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, including cloud-native architecture and services
- Strong knowledge of distributed systems, microservices, APIs, containerization, Kubernetes, and infrastructure automation
- Proven experience implementing enterprise MLOps and AgenticOps practices, including model deployment, monitoring, governance, and continuous delivery
- Hands-on experience with modern AI frameworks such as PyTorch, TensorFlow, Scikit-learn, LangChain, LangGraph, LlamaIndex, or equivalent technologies
- Experience architecting and deploying Agentic AI applications using LLMs, RAG, vector databases, AI agents, and model evaluation frameworks
- Strong understanding of AI governance, Responsible AI, security, privacy, and regulatory compliance
- Excellent communication, stakeholder management, and technical leadership skills
What You'll Deliver
- Enterprise AI platforms and applications that enable secure, scalable, and reusable AI capabilities across Mastercard
- Technical leadership that accelerates the adoption of AI while maintaining engineering quality, operational excellence, and governance
- Modern AI engineering practices that improve developer productivity, deployment velocity, and production reliability
- Strategic AI solutions that drive business innovation, operational efficiency, and customer value across the enterprise
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard's security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
Mastercard Pune, Mahārāshtra, IND Office
Poona Club Road, Pune, Maharashtra, India, 411001
Similar Jobs at Mastercard
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Secure identities for AI systems by discovering and inventorying AI/non-human identities, enforcing least-privilege lifecycle controls, implementing access policies, monitoring identity behavior, performing assessments and remediation, supporting governance and compliance, producing metrics and runbooks, and advising engineering teams on AI identity security best practices.
Top Skills:
Ai-SpmAPIsAttribute-Based Access Control (Abac)Cloud ProvidersContext-Aware AuthorizationCryptographic IdentitiesDelegated Authority ManagementIamIsoNistRole-Based Access Control (Rbac)Service AccountsShort-Lived CredentialingTelemetryZero Trust Architecture
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Supports global privacy compliance through OneTrust platform administration, privacy reviews of marketing promotions, and sub-processor inventory management. Responsibilities include managing privacy workflows and records, reviewing consent language and contractual provisions, tracking approvals, maintaining audit-ready data, generating reports and dashboards, coordinating with legal and business stakeholders, supporting audits, and improving processes. The role requires knowledge of global privacy principles, strong organization and communication skills, and experience in privacy operations, compliance, legal operations, risk management, or data governance.
Top Skills:
Microsoft 365ExcelMicrosoft PowerpointOnetrust
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
Leads the design, development, and delivery of scalable full-stack Java applications using React or Angular. Establishes architecture, technical standards, APIs, microservices, security, resiliency, and zero-downtime production practices. Collaborates with product and cross-functional teams, provides technical leadership, estimates scope and timelines, and supports project delivery. The role also drives cloud-native development, DevOps automation, observability, release management, and adoption of generative AI solutions.
Top Skills:
Angular 14+AnsibleApache AirflowAWSAws SqsAzureC#CamundaChefCi/CdDockerDroolsEasyrulesElasticsearchElk StackGCPGenerative AiGithub CopilotGradleGroovyHibernateHTMLInfrastructure As CodeJava 17+JavaScriptJenkinsKafkaKubernetesLarge Language ModelsMavenMicroservicesMongoDBN8NNetflix ConductorNode.jsOpenapiOpenshiftOpentelemetryOraclePostgresPythonRabbitMQReact Js 16+RedisRestRetrieval-Augmented GenerationScalaSonarqubeSplunkSpring BootSpring FrameworkSQL ServerUnix Shell Scripting
What you need to know about the Pune Tech Scene
Once a far-out concept, AI is now a tangible force reshaping industries and economies worldwide. While its adoption will automate some roles, AI has created more jobs than it has displaced, with an expected 97 million new roles to be created in the coming years. This is especially true in cities like Pune, which is emerging as a hub for companies eager to leverage this technology to develop solutions that simplify and improve lives in sectors such as education, healthcare, finance, e-commerce and more.
