Job Description
Job Description
Tools and Technologies You Might Use
- Cloud: AWS, Azure, GCP
- Containers: Kubernetes, Docker
- DevSecOps: GitHub Actions, GitLab CI, Azure DevOps, Terraform
- Security: SIEM, EDR, WAF, API gateways, secrets managers
- AI stack: model gateways, vector databases, model registries, ML pipelines
Examples of Work and Technical Scope
- Secure an LLM gateway with authentication, authorization, quotas, content filtering, and audit logging
- Add prompt injection defenses for an agent that uses tools like web search and internal APIs
- Implement retrieval filtering, context redaction, and output scanning for a RAG application
- Build model artifact signing and verification into the release pipeline
- Create detections in SIEM for abnormal model usage, including model scraping patterns
Required Qualifications
- Bachelor’s degree in Cybersecurity, Artificial Intelligence, Computer Science, or related highly technical field
- 5+ years in security engineering, application security, cloud security, or detection engineering
- Experience securing LLM-based applications, RAG systems, or agentic workflows
- Familiarity with adversarial ML concepts, such as prompt injection, model inversion, and model extraction
- Experience with one or more cloud platforms, AWS, Azure, or GCP
- Experience with Kubernetes and container security
- Hands-on experience with at least one programming language, Python preferred
- Strong understanding of AI, LLMs, API security, identity, secrets management, and cloud controls
- Experience building security controls into CI and CD pipelines
- Proven ability to lead cross-functional security work with engineering and product teams
- Effectively communicate complex technical concepts to both technical and non-technical stakeholders
- Effectively communicate to leadership and know when to escalate with proactive, clear, data-driven insight, highlighting risks, roadblocks, and solutions
- Proven leadership capabilities with the ability to influence and drive change
Preferred Qualifications
- Master’s degree in Cybersecurity, Artificial Intelligence, Computer Science, or related highly technical field
- AI/ML certifications (e.g., Microsoft Azure AI Engineer, AWS ML Specialty, GIAC Machine Learning Engineer, ISC2 Building AI Strategy)
- Experience with security telemetry and detections in SIEM or EDR platforms
Regards
Purvi Sonker
Sr Technical Recruiter