Senior Engineer, AI Cyber Security

Biogen

. Design, build, and operate detection capabilities for prompt injection, model extraction, training data poisoning, and adversarial input attacks .

Posted 10/8/2026full-timeRemote • United StatesSenior💰 $140,000 - $187,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI/ML Security, Cloud Security Engineering, and Application Security, with hands-on proficiency in Python and experience with AI/ML frameworks and cloud services. Capable of developing security standards, conducting risk assessments, and engineering automated security solutions.

Highest-signal resume keywords

AI/ML SecurityCloud Security EngineeringPython ProficiencyMITRE ATLAS KnowledgeCrowdStrike Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAI/ML FrameworksSageMakerAzure OpenAIDatabricksSecurity AutomationAdversarial TestingSecurity Architecture ReviewsModel Governance ControlsRisk Assessments

Tools & Technologies

CrowdStrikeMicrosoft DefenderOktaZscalerCyberArk

Industry Keywords

AI SecurityCybersecurity EngineeringApplication SecuritySecurity OperationsNIST AI RMFOWASP AI Top 10LLM ArchitecturesData Access ControlsIncident InvestigationThreat Correlation

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, build, and operate detection capabilities for prompt injection, model extraction, training data poisoning, and adversarial input attacks
Develop and maintain AI security monitoring pipelines correlating signals across LLM interactions, API gateways, and model inference endpoints
Engineer automated response playbooks including model quarantine, token revocation, and session termination
Research emerging AI attack vectors and translate findings into detection signatures and prevention controls
Operate and tune CrowdStrike AI Runtime Defense and Microsoft Purview AI governance controls
Implement security controls across AWS SageMaker, Azure OpenAI, Databricks, and internal ML pipelines
Secure model training environments through data access controls, compute isolation, artifact signing, and pipeline integrity verification
Engineer generative AI guardrails including content filtering, DLP integration, output validation, and session-level access controls
Design and enforce AI model governance controls including model registry security, version control integrity, and deployment approval gates
Perform security architecture reviews of new AI services and integrations
Conduct technical AI risk assessments using MITRE ATLAS, OWASP AI Top 10, and NIST AI RMF
Perform adversarial testing and red teaming of AI models and AI-integrated applications
Develop AI security standards, reference architectures, and secure development guidelines
Evaluate third-party AI services and vendor integrations for security posture, data handling, and supply chain integrity
Build AI-powered security tools and integrations for threat correlation, threat hunting, alert triage, and incident investigation
Contribute to internal AI capabilities including MCP server development, agent frameworks, and security data pipelines
Build and maintain security scoring engines and risk quantification models

Requirements

What you’ll need

5+ years of combined experience in cybersecurity engineering, software engineering, and/or AI/ML systems
Demonstrated expertise in at least three of the following domains: AI/ML Security; Cloud Security Engineering; Application Security; Security Operations
Hands-on proficiency with Python and demonstrable experience building production security tooling and automation
Experience with AI/ML frameworks including PyTorch, TensorFlow, Hugging Face, and LangChain
Experience with AI cloud services including SageMaker, Azure OpenAI, Bedrock, and Databricks
Working knowledge of MITRE ATLAS, OWASP AI Top 10, and NIST AI RMF
Experience with enterprise security platforms including CrowdStrike, Microsoft Defender, Okta, Zscaler, CyberArk, or equivalent
Strong understanding of LLM architectures, retrieval-augmented generation (RAG), fine-tuning security implications, and agentic AI patterns
Bachelor's Degree in Computer Science, Cybersecurity, Data Science, or related technical field required

Benefits

Comp & perks

Regular employees are eligible for short-term and long-term incentives, including cash bonus and equity incentive opportunities
Medical, Dental, Vision, & Life insurances
Fitness & Wellness programs including a fitness reimbursement
Short- and Long-Term Disability insurance
A minimum of 15 days of paid vacation
Additional end-of-year shutdown time off (Dec 26-Dec 31)
Up to 12 company paid holidays
3 paid days off for Personal Significance
80 hours of sick time per calendar year
Paid Maternity and Parental Leave benefit
401(k) program participation with company matched contributions
Employee stock purchase plan
Tuition reimbursement of up to $10,000 per calendar year
Employee Resource Groups participation