Security Engineer (AI Platform Engineering)

Join Saronic as a Security Engineer for AI Platform Engineering. In this role, you will build a secure and self-service AI platform, enabling teams across the company to use AI effectively and safely. You will partner with various departments, educate them on AI usage, and build complex AI solutions. This is a customer-facing role, and you will have the opportunity to define how the entire company uses AI safely and own AI governance and security from the ground up.

• Build and secure production systems for AI-powered applications, agents, and automations across the company.
• Teach teams to use AI safely and effectively, and set company-wide standards for good, safe AI usage.
• Own AI governance, visibility, and inventory; monitoring and logging of AI usage; and prompt- and output-level data-loss-prevention.
• Ability to obtain and maintain a U.S. security clearance
• Immense kindness and patience for supporting and teaching non-technical users
• Enough software and security foundation to build and secure production systems, with sound judgment on data handling and safe AI usage
• Working knowledge of the strengths and weaknesses of different AI models and platforms, and how to match the right model to a task
• You’re a genuine AI power user who builds: you’ve shipped agents, tools, or automations with LLMs, and you can walk through the hard parts
• Fluency with modern agent concepts: agentic loops, agent harnesses, context engineering, tool use / function calling, MCP, and evals
• We are not looking for degrees or certifications in Artificial Intelligence. We care about what you’ve built and what you can do. Self-taught practitioners and career-changers are welcome; this role is about outcomes and attitudes
• You build real backends and infrastructure, not just demos: APIs, data pipelines, authentication and secrets, hosting and deployment (containers, Infrastructure-as-Code, CI/CD), and systems integration, made reliable with observability, evals, and graceful failure handling
• Experience with AI governance, DLP, monitoring/logging, or guardrails for AI usage
• Building and hosting AI solutions in the cloud
• A security background (application, cloud, or data protection)
• Experience teaching, enabling, or supporting non-technical teams