Senior UI Developer

AI in this role

databricks

ml-ops

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

Senior UI Developer

Overview
Mastercard is seeking a UI Developer to join an AI product team building cutting edge foundation model capabilities with enterprise wide impact. You'll design and build the applications that bring advanced AI capabilities to life. Turning powerful, complex model outputs into clear, intuitive, and interactive experiences for the people who rely on them. You will join a team of AI Engineers, Software Developers, Data Scientists and MLOps to bring these capabilities to market.

In this role, you will be responsible for the design, development, and maintenance of the platform's frontend applications, spanning both internal tooling and external-facing self-service tools.

Key responsibilities:

Design and build advanced, interactive visualization tooling for embeddings and model outputs. Including exploratory views of embedding clusters/similarity (e.g., dimensionality-reduced spatial views), interactive drill-down, filtering, and comparison across model/embedding versions.
Design and build self-service applications for end users. Including submitting requests (e.g., filter-based embedding generation), tracking job status, and retrieving results, integrating against the platform's API layer.
Design and build prototypes for future product versions and executive level demos.
Design and build internal tooling for own AI teams, to streamline product advancement.
Build and maintain applications on Databricks App hosting, including understanding its deployment model, constraints, and integration points with Unity Catalog and the platform's own APIs.
Integrate frontend applications against the platform's API layer, working closely with the Software Engineers to align on contract, authentication, and versioning as the API evolves.
Collaborate with Lead Data Engineer and Senior AI Engineer on internal tooling requirements, translating their workflow needs into practical, well-designed interfaces.
Own frontend code quality and maintainability. Component structure, testing, and documentation, to a standard consistent with the rest of the engineering team's practices.
Design with the platform's varied user base in mind. From highly technical internal AI engineers to product/software teams who may have less context on the underlying model architecture.
Contribute to frontend architecture decisions as the platform's application surface grows, including recommending patterns and tooling within what Databricks Apps and the organization's standards support.
Support production issues affecting frontend applications, including troubleshooting and coordinating with backend roles when an issue spans both layers.

All About You
Required skills and experience:

Strong, production-level frontend development experience in React, and/or Python-based data-app frameworks (Streamlit or Dash).
Component architecture, state management, and building applications meant to be maintained and extended over time, not one-off prototypes.
Experience integrating frontend applications against REST APIs. Including handling authentication, asynchronous job patterns (submit, poll/callback, retrieve), and designing around API versioning.
Familiarity with visualization libraries capable of advanced/interactive rendering (e.g., D3.js, deck.gl, Plotly, or similar).
Familiarity with Databricks Apps as a hosting/deployment model, including its constraints and how it serves React, Streamlit, and Dash applications specifically. Direct Databricks experience is a strong plus.
Advanced data visualization experience, including interactive/exploratory tooling. Not just static charts, but genuinely interactive interfaces: filtering, drill-down, dynamic re-rendering, and ideally experience visualizing high-dimensional or embedding-style data.
Comfortable designing for mixed technical audiences. From AI engineers who want dense, fast access to detail, to end users who need simplicity and guardrails.
Fluency reading/writing SQL or querying a governed data platform (e.g., Unity Catalog).
Strong UI/UX instincts. Able to make reasonable design decisions independently rather than needing every interaction pattern specified, while knowing when to loop in design/product input.
Solid testing and code quality practices for frontend code. Component/unit testing, and comfort working within CI/CD pipelines the rest of the team maintains.
Clear communicator, able to work directly with backend, data, and AI engineering roles to understand what an interface actually needs to expose.
Comfortable operating in a fast-moving, evolving environment.

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

Senior UI Developer at Mastercard rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● 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. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsDatabricks

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through how you've used Databricks in your day-to-day work.
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: ML Ops and Databricks. 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.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.

Get new AI jobs (Works on AI ●●●○ or higher) by email

One email a week with the new AI jobs (Works on AI ●●●○ or higher), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Also alert me for new jobs at Mastercard

Free. One email a week. Unsubscribe in one click.