Security Engineer

Productive Playhouse•Glendale, CA

2d•$120,000 - $130,000•Remote

About The Position

Productive Playhouse is seeking a Security Engineer with hands-on AI/ML experience to lead and strengthen our security posture as we scale AI-driven transcription, translation, and quality assurance workflows across global operations. This role is critical to ensuring our AI systems, cleanroom environments, and enterprise infrastructure meet the highest standards of security, compliance, and client trust. The Security Engineer will serve as a technical leader bridging cybersecurity engineering and AI systems governance, designing resilient architectures, mitigating emerging AI threats, and enabling secure innovation across the organization. This position plays a key role in supporting enterprise client audits, ISO/SOC compliance initiatives, and internal AI governance frameworks.

Requirements

4+ years of cybersecurity engineering experience
Minimum 2 years working in AI/ML systems or data science infrastructure
Strong understanding of AI/ML security risks including adversarial ML, prompt injection, data leakage, and model supply chain vulnerabilities
Hands-on experience with cloud security (AWS, GCP, or Azure), container security, and CI/CD pipeline hardening
Proficiency in Python and scripting for security automation and AI/ML tooling
Working knowledge of at least one ML framework (PyTorch, TensorFlow, or similar) and familiarity with LLM architectures
Experience with compliance frameworks such as ISO 27001, SOC 2, or NIST 800-171
Familiarity with endpoint protection, SIEM, network security tools, and identity/access management
Strong analytical and communication skills with the ability to translate technical risks into business impact

Nice To Haves

Relevant certifications such as CISSP, CCSP, CEH, OSCP, or AI/ML-specific security credentials
Experience securing multi-language NLP or speech recognition systems
Background in securing annotation and labeling platforms for ML training data
Experience with GitHub Enterprise security configurations, secrets management, and repository access controls

Responsibilities

Design and implement security controls for AI/ML pipelines, including model training environments, inference endpoints, and data preprocessing workflows
Develop threat models specific to AI/ML systems (such as prompt injection, data poisoning, model extraction, and adversarial attack vectors)
Build monitoring and anomaly detection systems for AI model behavior, data drift, and unauthorized access patterns
Secure third–party AI platforms and APIs in alignment with ISO 27001 and SOC 2 controls
Support secure deployment of agentic AI capabilities across production environments
Harden cloud infrastructure (AWS, GCP, or Azure) and containerized workloads
Implement CI/CD security controls and secrets management best practices
Manage endpoint protection, network security, and identify and access management solutions
Maintain and continuously improve secure cleanroom environments for sensitive client data in accordance with existing playbooks and frameworks.
Implement and optimize SEMM integrations, log monitoring, and alert workflows
Develop and maintain A security standards, policies, and SOPs
Support ISO 27001, SOC 2, and NIST-aligned security programs
Conduct vendor security assessments for AI and SaaS platforms
Support enterprise client security questionnaires, audits, and due diligence reviews
Partner cross-functionally with HR, Governance, and Operations on risk mitigation
Support security incident response and forensic investigations
Conduct vulnerability assessments and penetration testing
Identify systemic risk exposure and implement preventative controls
Translate technical risk findings into business impact summaries for leadership.
Perform additional security-related duties, projects, and initiatives as assigned, consistent with the scope, level, and evolving needs of the organization. The employee is expected to demonstrate flexibility and ownership in supporting organizational security priorities.