AI Security Engineer (AI & Agentic Security)

What You'll Need
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.