Senior Manager, AI Platform Engineering

🇺🇸 Carson City, Nevada
Posted 2 months ago
Expires May 29, 2026
Full TimeRemote

WHY SOCURE?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.

At Socure, our AI Platform team turns cutting-edge models into real-world systems, serving customers at massive scale.

We’re seeking a Senior Manager of AI Platform Engineering to lead the team responsible for building, scaling, and operating the systems that power our entire ML lifecycle. If you are a technical leader who understands distributed systems, values strong platform design, and is motivated by enabling data scientists and engineers to deliver models to production with speed, reliability, and confidence, this might just be the place for you.

You will define the roadmap for our ML platforms and tooling, guide engineering execution, establish best practices, and ensure that Socure’s model development and deployment processes are secure, governed, built for scale, and best-in-class.

KEY RESPONSIBILITIES

PLATFORM VISION & STRATEGY

- Develop and own the roadmap for Socure’s AI/ML platform, including data and feature engineering workflows, training infrastructure, experimentation tooling, model deployment/serving, monitoring, and governance.

- Define architecture and standards that create clear, scalable, and secure paths for building and operating AI systems.

- Assess technology options and drive consolidation across the company to reduce fragmentation and improve consistency across the ML too...

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