AI Security Engineer (AI & Agentic Security)

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OtherAi Security Engineer

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Quick Summary

Requirements Summary

Direct experience with MCP (Model Context Protocol) or A2A protocol security, or with AI gateway products (Kong AI Gateway, Azure APIM GenAI Gateway, Apigee).

Technical Tools

OtherAi Security Engineer

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.

Nice to Have

~1 min read

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.