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Capacity is an AI-powered support automation platform that helps teams work better through intelligent process automation. The company has raised over $100M from 150+ investors and is building enterprise-grade SaaS infrastructure.
This role offers a unique opportunity to work at the intersection of high-performance AI and privacy. You will design the future of secure intelligence by solving the industry's most urgent challenge: executing powerful AI models while maintaining cryptographic certainty and absolute data isolation.
As a Secure AI Software Engineer, you will take ownership of microservices integration and architecture that powers the company's highly secure inference platform. Your mission includes implementing sophisticated attestation mechanisms, protecting critical model weights, and enforcing execution boundaries. You will translate complex security protocols into fluid, high-performance reality.
Key responsibilities include designing and implementing secure inference pipelines, architecting microservices for confidential computing environments, developing attestation and verification systems, optimizing performance within security constraints, and collaborating with security and ML teams to ensure end-to-end protection. You will work on cryptographic integration, trusted execution environment (TEE) orchestration, and building systems that guarantee data isolation while maintaining inference speed.
The ideal candidate has strong systems engineering experience, deep understanding of cryptography and secure computing, expertise with microservices architecture, and proven ability to balance security with performance. Experience with confidential computing platforms, TEEs, or secure enclaves is valuable. You should be comfortable working in a fast-paced environment pushing the boundaries of what's possible in secure AI infrastructure.
