Principal Software Engineer – Next-Generation API & AI Platform Architecture

<div class="content-intro"><p>SpyCloud is on a mission to make the internet a safer place by disrupting the criminal underground. SpyCloud’s solutions thwart cyberattacks and protect more than 4 billion accounts worldwide. Cybersecurity is an exciting, evolving space, and being at the forefront of the fight to disrupt cybercrime makes SpyCloud a special place to work. If you’re driven to align your career with a fantastic mission, look no further!</p></div><p><strong>*The ideal candidate for this role would work hybrid (2 days per week) in our Austin, Texas headquarters. We are also open to candidates who are remote in the United States, but can travel to our headquarters 1-2 times per quarter*</strong></p> <p>We are seeking a Principal Engineer to lead the hands-on architecture and development of our next-generation data and intelligence APIs. This role is deeply technical and execution-focused, responsible for defining API contracts, building production services, and architecting the platform interfaces high-performance throughput, agentic workflows, and external customer integrations.</p> <p>You will operate at the intersection of distributed systems, data platforms, and agentic orchestration, ensuring our APIs are scalable, governed, observable, and designed for long-term evolution. This role requires strong systems thinking, high-quality implementation standards, and the ability to translate platform strategy into production-grade services.</p> <p>This is a hands-on engineering role with architectural authority.</p> <p> </p> <p><strong>What You'll Do:</strong></p> <ul> <li>Next-Generation API Architecture</li> <ul> <li>Architect and implement customer-facing data and intelligence APIs with clear versioning, SLAs, and backward compatibility.</li> <li>Define and enforce API contracts for:</li> <ul> <li>Low latency, high throughput endpoints</li> <li>Agentic workflows (tools, actions, state transitions, handoffs)</li> <li>Context retrieval and enrichment</li> </ul> <li>Design APIs as durable platform interfaces, not thin wrappers over storage systems.</li> <li>Establish standards for schema governance, payload design, and service boundaries.</li> </ul> <li>Agentic & ML Platform Integration</li> <ul> <li>Architect service layers that support agentic workflows, including orchestration interfaces, guardrails, and runtime observability.</li> <li>Build API surfaces that expose model outputs safely and consistently.</li> <li>Collaborate with MLEs and Data Scientists to move models from experimentation into robust inference services.</li> <li>Ensure proper lifecycle management, monitoring, and