Generative Ai Security Evaluation Cybersecurity Jobs

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Security Engineer, AI Platform Engineering

Saronic Technologies San Diego, CA

San Diego, CA

Today

Full time Agent Agentic Ai Ai Security

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Job Description

Saronic Technologies is hiring a Security Engineer for AI Platform Engineering in San Diego, CA (onsite). This role helps make AI safe and self-service across the organization by delivering secure-by-default platform capabilities, establishing governance, and enabling teams to use AI appropriately.

Responsibilities

Build AI-powered applications, agents, and automations for teams across the company using Saronic’s cloud platforms, with production-grade backends, infrastructure, and integrations tied to real data and systems.
Deliver hardened, compliant, well-hosted, secure-by-default solutions that prevent insecure ad-hoc “vibe-coded” tooling from being shipped independently by departments.
Teach teams to use AI safely and effectively in their own work, and set company-wide standards for safe AI usage.
Own AI governance, visibility, and inventory, including monitoring and logging of AI usage and prompt- and output-level data-loss-prevention to protect sensitive information, including customer data.
Implement guardrails for AI usage by treating AI agents as identities with least privilege, governing model and agent access, and ensuring the approved approach is the easiest option to reduce “shadow AI.”
Build agents and workflows that operate reliably, including tool design and MCP integrations, context and memory management, and quality validation through evaluative loops.
Represent the AI security and platform engineering team across the organization, partnering with internal teams to understand their goals, support safe adoption, and build solutions requiring real engineering, security guardrails, and proper hosting.
Enable broader business use of AI by putting the right guardrails and visibility in place and delivering more complex, securely hosted AI solutions for ideas that need governance and reduced risk.

Requirements

Demonstrated AI power-user experience building with LLMs, including shipped agents, tools, or automations, with the ability to explain the hard parts.
Experience building real backends and infrastructure beyond demos, including APIs, data pipelines, authentication and secrets, hosting and deployment (containers, Infrastructure-as-Code, CI/CD), and systems integration supported by observability, evals, and graceful failure handling.
Fluency with modern agent concepts such as agentic loops, agent harnesses, context engineering, tool use and function calling, MCP, and evals.
Working knowledge of model and platform strengths and weaknesses, including matching the right model to a task.
A sufficient software and security foundation to build and secure production systems, with sound judgment on data handling and safe AI usage.
Immense kindness and patience when supporting and teaching non-technical users.
Ability to obtain and maintain a U.S. security clearance.
No requirement for degrees or certifications in Artificial Intelligence; focus is on outcomes and what the candidate has built and can do. Self-taught practitioners and career-changers are welcome.

Technologies

LLMs
Cloud platforms
APIs, data pipelines
Authentication, secrets
Containers, Infrastructure-as-Code, CI/CD
Observability, evals
Agentic loops, agent harnesses
Context engineering, tool use, function calling
MCP
Prompt- and output-level data-loss-prevention

Preferred Qualifications

Experience with AI governance, DLP, monitoring/logging, or guardrails for AI usage.
Experience building and hosting AI solutions in the cloud.
A security background, including application, cloud, or data protection.
Experience teaching, enabling, or supporting non-technical teams.

How You Work

Kind and patient by default: meet people where they are, provide generous answers for basic questions as well as complex ones, and avoid making others feel small.
Low-ego and intellectually humble: explain technical ideas to non-technical colleagues without condescension, share when you do not know, and take ownership of mistakes with strong opinions held loosely.
A natural teacher and enabler: focus on increasing colleague capability, turning one-off help into reusable guidance and patterns.
Deep empathy and listening: start from the person’s actual problem and act as a voice of the user to partner effectively with security and platform teams.
Values-aligned and high-agency: collaborate with integrity across engineering, security, legal, and business teams while navigating ambiguity.

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