How to apply for Staff Software Engineer

About OpenMined

OpenMined is a nonprofit building AI governance infrastructure and a public network for non-public data. Its products, Syft Space and Syft Hub, let data owners publish content under their own terms and let AI query it live with attribution. This is a chance to work on an alternative to the copy-everything-into-weights model that much of the AI stack uses today.

About the role

You lead the Network Sourced AI squad as the most experienced engineer, writing code and making architecture decisions for Syft Space and Syft Hub. Syft Space is the local node data owners run to publish content with their own pricing and terms. Syft Hub is the network layer that lets AI labs, agents, and app developers find and query those nodes in real time. The role is team lead plus hands-on technical leadership, setting engineering standards by example and connecting squad decisions to the broader platform strategy.

A typical day

A typical day likely mixes writing and reviewing code for Syft Space or Syft Hub with architecture discussions and unblocking other engineers on the squad. You would also spend time connecting squad decisions to the organization's broader platform strategy. The exact routine is not described in the posting, so ask about meeting cadence, on-call, and how the squad ships during interviews.

Who OpenMined is looking for

• Senior or staff-level engineer who still writes production code and makes architecture decisions daily.
• Has led a small engineering team or squad and set engineering standards by example.
• Experienced building production software that ships continuously, not just prototypes or research code.
• Comfortable working on networked, distributed systems where data stays at the source and queries happen live.
• Can connect technical decisions on a squad to an organization-wide platform strategy.

Tips for this application

• Read the OpenMined site and the Syft Space and Syft Hub product descriptions before writing anything. Reference how the two products fit together in your application.
• Show production shipping experience explicitly. The job description asks for a squad that ships production software continuously, so name systems you shipped and maintained, not just designed.
• Describe a time you led a team while remaining hands-on. Give the size of the team, your coding contribution, and the architecture decisions you made.
• Address the data-stays-at-source architecture directly. Explain why you think querying live data with attribution differs from copying content into model weights, and where you have built something similar.
• Since this is a nonprofit with a stated mission, connect your work history to open, equitable, and accessible data. Keep it factual, not promotional.

What to cover in your cover letter

['Your experience as the most senior engineer on a team, including both code you wrote and standards you set.', 'Concrete examples of production systems you shipped and how you kept delivery continuous.', 'Any work on distributed or networked systems, especially where data ownership, access control, or attribution mattered.', "How you would connect the Network Sourced AI squad's decisions to OpenMined's broader platform strategy."]

Research before applying

• Read the OpenMined site and any public material on Syft Space and Syft Hub to understand the two products and how they connect.
• Look into OpenMined's stated goal of building AI governance infrastructure and what that means for its roadmap.
• Find public talks, papers, or repositories from OpenMined engineers to see how the team builds and what stack it uses.
• Check how the organization is funded and structured as a nonprofit, since that affects how engineering priorities get set.

Likely interview topics

Based on the job description, expect questions about:

• How you would architect a local node like Syft Space that publishes content under owner-set terms and pricing.
• How Syft Hub would let AI labs and agents discover and query across many nodes in real time, and what the failure modes are.
• A time you led a squad and had to raise its ability to ship production software continuously.
• How you make architecture decisions when you are the most experienced engineer and others look to you for production-quality judgment.
• How attribution back to data owners would work end to end, and how you would test or verify it.

Common mistakes to avoid

• Applying as a manager who no longer codes. The role explicitly requires writing code and making architecture decisions.
• Treating it as a research or pure ML role. The work is production software for a network of data nodes, not model training.
• Ignoring the nonprofit context and writing as if this were a standard for-profit product role. The mission and governance angle are central to the products.