AI Security Engineer (AI & Agentic Security)
At a glance
Mid-level Security Engineering role at Strategic Systems International. Remote, Mexico · contract.
Pay not stated AI Security Engineer salary
remoteroles summary, based on the employer's posting.
What you'll do
- Assess AI tools and workflows, then shape controls that support safer adoption across the organization
- Turn AI risks into testable security policies and automated checks in pipelines, gateways or data-loss controls
- Examine new tools, protocols and frameworks to understand their architecture, trust boundaries and authentication
- Write clear control requirements from vendor gaps or tool risk assessments so others can implement and test them
What you bring
- At least five years in software engineering, with Python or a comparable language
- Three or more years in AI security, or hands-on infosec experience paired with a demonstrated move into AI security
- You can convert specific security policies into automated enforcement, not just written guidance
- You have cloud security experience across at least two of AWS, GCP and Azure, plus regulated-industry compliance experience
Who this fits
This mid-level contract role suits a hands-on engineer who can investigate unfamiliar AI technologies independently and make defensible security calls quickly. The role is remote in Mexico.
From the employer
AI Security Engineer — AI & Agentic Security
We are seeking an experienced, hands-on, AI Security engineer / developer, to support our Enterprise AI Security Program. Our AI landscape spans everything from internal chatbot pilot to a full agentic workflow with tool access, Code Assistant rollout to thousands of developers to new Agentic platform. Externally, the tools and protocols worth worrying about change every few months. You'll be the person who can look at both ends of that spread ensuring safe and secure adoption of AI.
Required:
- Strong SWE, with 5+ years of experience; proficiency in Python (or equivalent)
- 3+ years in AI/ML or GenAI security (prompt injection defense, unsafe output handling, tool-use abuse, data leakage), or equivalent hands-on infosec experience with a demonstrated pivot into AI security.
- Demonstrated ability to write security policy that is specific and testable, and to translate it into automated enforcement (policy-as-code, CI/CD gates, gateway-level controls, DLP rules) rather than a document that relies on voluntary compliance.
- A track record of self-directed learning on fast-moving technical topics — comfortable digging into how a brand-new tool, protocol, or framework actually works (architecture, trust boundaries, auth model) well enough to give a defensible security opinion on it within days, not months.
- Working knowledge of AI/LLM security risks: prompt injection, jailbreaking, unsafe outputs, tool-use abuse, identity misuse, agentic workflow escalation.
- Hands-on familiarity with AI security frameworks: NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10 / OWASP Agentic Top 10.
- Experience with cloud security across at least two of AWS, GCP, and Azure, including native AI/ML security tooling (Bedrock Guardrails, Vertex AI floor settings, Azure AI Content Safety).
- Identity and access management fundamentals — OAuth 2.0/2.1, OIDC, mTLS — with interest in or exposure to non-human/workload identity (SPIFFE/SPIRE) and agent identity models.
- Experience in a highly regulated industry (healthcare, financial services) with HIPAA or equivalent compliance obligations.
- Strong technical writing — you can turn a vendor capability gap or a new tool's risk profile into a control requirement someone else can implement and test.
Preferred:
- Direct experience with MCP (Model Context Protocol) or A2A protocol security, or with AI gateway products (Kong AI Gateway, Azure APIM GenAI Gateway, Apigee).
- Exposure to AI-native runtime security platforms (Straiker, Palo Alto Prisma AIRS, Virtue AI) or classic content guardrail products.
- Familiarity with shadow-AI / BYOAI risk — e.g., locally-run autonomous agent frameworks (OpenClaw and similar), unsanctioned browser extensions, personal AI accounts used for work — and how to discover and govern them at scale (CrowdStrike Falcon, Wiz, CASB, or similar).
- AI red-team tooling experience (PyRIT, Promptfoo, AgentDojo, or custom harnesses).
- Familiarity with Microsoft Purview DSPM for AI or equivalent DLP-for-AI tooling.
- Relevant certification (CAISP, ISACA AAISM) or equivalent demonstrated skill.
- Experience with detection engineering, SIEM integration, and telemetry design for AI/agent behavior.
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