AI Engineer ||

Mastercard is hiring an AI Engineer ||. Level rates it ; you can apply on Mastercard.

Level's read on this job

Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
The posting mentions Copilot and prompt engineering among its tools and skills.
Mastercard has 967 other open roles on Level.
Posted in the last few days.

AI in this role

Copilot

prompt-engineering

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

AI Engineer ||

Role Summary
The AI Engineer is responsible for designing and delivering AI-powered solutions that improve engineering productivity and business workflows. This role requires a strong foundation in AI/ML concepts, with hands-on expertise in LLM systems, data preparation, and context design (including chunking) to build scalable, high-quality AI solutions.

What You Will Do
Lead AI-Driven Solution Development

Identify and drive high-impact AI use cases across engineering and business workflows
Design end-to-end AI solutions leveraging LLMs, orchestration, and automation
Move rapidly from exploration to production-grade implementations

Build LLM Solutions & Intelligent Agents

Develop LLM-based applications including prompt frameworks, orchestration layers, and integrations
Create and evolve AI-powered agents (e.g., Copilot-based or similar) for workflow automation and decision support
Apply techniques such as retrieval-augmented approaches, context management, and prompt optimization

Design Data, Context & Chunking Strategies (Critical)

Structure and prepare data for LLM consumption, including effective chunking and context window optimization
Design retrieval strategies that improve relevance, accuracy, and response quality
Balance context size, latency, and cost while maintaining solution effectiveness

Apply Strong AI/ML Foundations

Understand and reason about model behavior, evaluation, bias, and limitations
Tune and adapt prompts, context, and workflows instead of relying on model retraining
Ensure responsible and effective use of AI through sound engineering practices

Drive Engineering Productivity with AI

Apply AI tools (e.g., Copilot and similar) to improve developer velocity and quality
Build reusable patterns for AI-assisted coding, testing, and documentation
Measure and scale productivity impact across teams

Data & Application Engineering

Build data pipelines and integrations to support AI workflows
Develop APIs, services, and applications embedding AI capabilities
Ensure solutions are scalable, maintainable, and integrated into real workflows

What You Bring

Strong foundation in AI/ML concepts, especially LLMs and modern AI systems
Hands-on experience with:

Prompt engineering and LLM orchestration frameworks
Context design, chunking strategies, and retrieval techniques
Working with structured and unstructured data for AI use cases

Solid software engineering and system design experience
Ability to build end-to-end AI solutions (data → context → LLM → application)
Pragmatic mindset focused on quality, usability, and business impact

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

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.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 02/02/2027. If the fill date has passed, Mastercard intends to fill this position as soon as possible.

Pay Ranges

O'Fallon, Missouri: $92,000 - $147,000 USD

How we rate this

AI Engineer || at Mastercard rates 89 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

AI Engineer || is an open job at Mastercard.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in O'Fallon, Missouri.
The job was posted on November 4, 2026.
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

Prompt engineeringCopilot

Also common in AI engineer jobs at this level

Python AI agents AWS Machine learning Generative AI Azure

Pay

Typical AI engineer job: $182k

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 do you structure and test a prompt to get consistent output from a language model?
Walk me through how you've used Copilot in your day-to-day work.
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: Prompt engineering and Copilot. 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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