Security Engineer, AI Platform Engineering
Saronic
| Company | Saronic |
| Category | Engineering |
| Location | Austin |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 15 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
Saronic Technologies is a leader in revolutionizing autonomy at sea, dedicated to developing state-of-the-art solutions that enhance maritime operations through autonomous and intelligent platforms.
Security at Saronic is a force multiplier, not a blocker. AI is being adopted fast across our company, and we’re looking for a Security Engineer for AI Platform Engineering to make AI both safe and self-service. Think of this as a platform and enablement function for AI: you’ll build the paved, secure road so teams don’t have to take the shadow one. You’ll help e peoplacross the business use AI well, put the right guardrails and visibility in place, and build the more complex, well-hosted, secure AI solutions that departments need so great ideas get built properly instead of turning into ungoverned risk and liability.
This is a customer-facing role, and your customers are your colleagues in every department. You’ll partner with teams across the company to understand what they’re trying to accomplish, teach them to use AI effectively and safely, and build the solutions that need real engineering, security guardrails, and proper hosting.
This is an opportunity to define how an entire company uses AI safely, and own AI governance and security from the ground up, and build AI applications that make every department more capable.
How we think about building with AI. Anyone can make a demo now. A good-looking front
end is nearly free, AI will generate a slick dashboard from a one-line prompt, and it will look
impressive in a meeting. That is the easy part. The real skill, and what this role is about, is
using AI to build robust backends, infrastructure, and integrations, wired to real data and
real systems, that reliably solve a business problem in production. We hire people who can
tell the difference between something that looks like it works and something that works, and
who are drawn to the second.
What You’ll Do
- Enable Departments and Build: Build AI-powered applications, agents, and automations for
teams across the company on our cloud platforms, with real backends, infrastructure, and
integrations to real data and systems, for properly hardened, compliant, well-hosted, secure-by-default solutions, so departments don’t ship insecure ad-hoc vibe-coded tools themselves.
- Educate & Set Standards: Teach teams to use AI safely and effectively for their own work,
and set company-wide standards for good, safe AI usage.
- Govern: Own AI governance, visibility, and inventory; monitoring and logging of AI usage;
and prompt- and output-level data-loss-prevention to protect sensitive data, including
customer data.
- Guardrails: Put guardrails in place for AI usage, treat AI agents as identities with least
privilege, govern model and agent access, and make the sanctioned path the best path so
“shadow AI” doesn’t take hold.
- Craft Reliable AI: Build agents and workflows that actually work, design tool use and MCP
integrations, manage context and memory, and validate quality with evaluative loops.
How You Work
- How you work matters as much as what you build. This role represents our team to the
entire company, so we’re looking for someone who is genuinely energized by teaching and
unblocking people, not someone who wants to be the smartest person in the room. You’ll
thrive here if you are:
- Kind and patient by default. You meet people where they are, answer the “basic”
question as generously as the hard one, and never make someone feel small for not
knowing something. You stay with people through the problem instead of handing off
a fix and making it someone else’s problem.
- Low-ego and intellectually humble. You explain technical ideas to non-technical
colleagues without condescension, you say “I don’t know, let’s find out,” and you own
your mist
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