Principal AI Engineer

Posted 2 Hours Ago
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Gurugram, Haryana, IND
Hybrid
Entry level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Leads the architecture, development, and operationalization of enterprise AI and agentic systems. Builds AI-ready data products, retrieval pipelines, vector stores, knowledge systems, and scalable data platforms. Establishes agent orchestration, observability, evaluation, and AgenticOps practices. Partners with data science, data engineering, and product teams to deliver secure, reliable AI solutions at scale, with emphasis on payment fraud detection and responsible AI.
Summary Generated by Built In
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
Principal AI Engineer
AI Solutions, part of Mastercard's AI & Data organization, scales AI across the enterprise, moving use cases beyond pilots into trusted, production-grade capabilities embedded in Mastercard's platforms and products. Centralizing this capability drives speed to scale, operational resilience, consistent delivery standards, and responsible AI by design, in close partnership with the AI Center of Excellence.
Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.
You will be joining a team of AI and data engineers working on innovative AI and ML fraud solutions. Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech and payments processing. We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge AI model evaluation and reporting processes.
NOTE: This role will be reporting to the VP of AI Engineering for AI Solutions.
As a Principal AI Engineer, you will:
Lead the architecture, design, and implementation of enterprise AI and agentic systems, ensuring scalability, reliability, and security.
Build and manage AI-ready data products, retrieval pipelines, vector data stores, and knowledge systems that power AI solutions.
Develop and standardize agent engineering capabilities, including orchestration, tool integration, memory management, and multi-agent workflows.
Establish AI observability, evaluation, and AgenticOps practices, including tracing, monitoring, and performance measurement of AI systems.
Partner with Data Science, Data Engineering, and Product teams to accelerate the delivery and operationalization of AI solutions across the enterprise.
All About You
Deep expertise in Data Engineering, AI Engineering, or Machine Learning platforms, with a proven track record of delivering production-grade AI solutions at scale.
Strong understanding of modern AI architectures, including retrieval-augmented generation (RAG), vector databases, agent frameworks, orchestration patterns, and LLM-powered applications.
Experienced in designing and building scalable data pipelines, data products, APIs, and distributed systems that support AI and analytics workloads.
Demonstrated technical leadership with the ability to influence architecture decisions, mentor engineers, and drive the adoption of engineering best practices across teams.
Passionate about solving complex business problems through innovation, with a pragmatic approach to balancing speed, quality, security, and operational
Proven ability to translate emerging AI capabilities into enterprise-scale platforms, reusable services, and measurable business outcomes.
At least an undergraduate degree in CS, or a STEM related field
Prior experience in payment fraud detection modeling
Nice to have:
PhD/Master's in CS, Data Science, Machine Learning, AI or a related STEM field
Experience in with data engineering and model building in PySpark using Spark ML on petabyte scale data
Understands and implements methods to evaluate own work and others for bias, inaccuracy, and error
Loves working with error-prone, messy, disparate, unstructured data
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.

Skills Required

  • Undergraduate degree in Computer Science or a related STEM field
  • Deep expertise in data engineering, AI engineering, or machine learning platforms
  • Proven experience delivering production-grade AI solutions at scale
  • Strong understanding of RAG, vector databases, agent frameworks, orchestration patterns, and LLM-powered applications
  • Experience designing scalable data pipelines, data products, APIs, and distributed systems
  • Technical leadership experience influencing architecture decisions and mentoring engineers
  • Ability to translate emerging AI capabilities into enterprise-scale platforms and reusable services
  • Prior experience in payment fraud detection modeling
  • Master's or PhD in Computer Science, Data Science, Machine Learning, AI, or a related STEM field
  • Experience with data engineering and model building in PySpark using Spark ML at petabyte scale
  • Ability to evaluate work for bias, inaccuracy, and error
  • Experience working with messy, disparate, unstructured data

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support — Retirement plans are highlighted as especially strong, featuring a notably generous company match and added financial-planning resources. Feedback suggests this component stands out as a key strength of the overall package.
  • Parental & Family Support — Parental and family benefits are consistently portrayed as robust, including extended new-parent leave and assistance for fertility, adoption, and surrogacy. Feedback suggests these programs are a signature part of the offering.
  • Leave & Time Off Breadth — Paid time off is described as substantial, with multiple leave types and generous vacation and personal days noted in U.S. materials. Feedback suggests time off is frequently praised as a differentiator.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

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