Principal AI Engineer

Mastercard is hiring a Principal AI Engineer in Gurugram, India. Level rates it ; you can apply on Mastercard.

Level's read on this job

Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
Tools and skills the posting cites include RAG, AI evaluation and AI safety.
Level classifies it as a lead role.
Level lists 1,100+ other open roles at Mastercard.
The role was posted in the last few days.

AI in this role

ragai-evaluationai-safety

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.

How we rate this

Principal AI Engineer at Mastercard rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Principal AI Engineer is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Gurgaon, India.
The job was posted on October 21, 2026.
Seniority: lead.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI EvaluationAI Safety

Also common in AI engineer jobs at this level

Python AWS AI agents Generative AI Azure Google Cloud

Pay

Typical AI engineer job: $183k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide that one model's output is better than another's for a given task?
How do you think about the risk of an AI system in this kind of role failing silently?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: RAG, AI Evaluation, and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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