Data Technical Architect, MongoDB Sharding - US Remote

July 17, 2026

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At Hugging Face, we’re on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 5 million users & 100k organizations who collectively shared over 1M models, 300k datasets & 300k apps. Our open-source libraries have more than 400k+ stars on Github.

About the Role

This is not an "ivory tower" architect role. We are looking for a hands-on leader who thrives on seeing their designs through to production. You will serve in a key technical role for our data layer, working alongside the rest of our engineering team to design, build, and scale our core database system.

What You'll Do:

Shape the Architecture: Collaborate closely with engineering and product teams to design and evolve the end-to-end architecture for our MongoDB environment, ensuring scalability, reliability, and performance.
Get Your Hands Dirty: Dive deep into our application codebase when needed to make specific, planned changes to the data access layer, queries, and services to support the architecture evolution.
Champion Best Practices: Develop and promote best practices for data modeling, schema design, and query performance.
Troubleshoot and Optimize: Serve as a subject matter expert for complex database performance issues, partnering with teams to diagnose, resolve, and learn from production incidents.
Enable the Team: Develop scripts, documentation, and automation that empower developers to work more effectively and safely with the database.

About you

4+ years of experience in data engineering or architecture, with a significant, up-to-date focus on MongoDB.
Proven, hands-on experience designing and implementing MongoDB sharding in a production environment. You should be able to discuss the trade-offs of different shard keys you've used in the past.
Strong proficiency in at least one modern programming language (Typescript/Node.js preferred), with demonstrated experience making changes to an application codebase.
A strong collaborative mindset with a history of working effectively in cross-functional teams to achieve shared goals.
Deep, practical understanding of MongoDB internals, including the aggregation framework, storage engines, indexing, and replication.
Excellent async/written communication skills with the ability to facilitate technical discussions and build consensus.

Preferred (Nice-to-Haves):

Experience with Infrastructure as Code (IaC) tools like Terraform or Pulumi.
Experience with running MongoDB in Atlas.
Familiarity with other database technologies (e.g., PostgreSQL, Redis, Elasticsearch).
Experience with large-scale data migration projects.

If you're interested in joining us but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact.

More about Hugging Face

We are actively working to build a culture that values diversity, equity, and inclusivity. We are intentionally building a workplace where you feel respected and supported—regardless of who you are or where you come from. We believe this is foundational to building a great company and community, as well as the future of machine learning more broadly. Hugging Face is an equal opportunity employer, and we do not discriminate based on race, ethnicity, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or ability status.

We value development. You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to grow continuously. We provide all employees with reimbursement for relevant conferences, training, and education.

We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.

We support our employees wherever they are. While we have office spaces in NYC and Paris, we're very distributed, and all remote employees have the opportunity to visit our offices. If needed, we'll also outfit your workstation to ensure you succeed.

We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.

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