Security Architect

o9 Solutions, Inc.; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

o9 Solutions, Inc. is seeking a Senior AI Security & MLSecOps Architect to lead the next generation of AI-native security at the company.

You will secure GenAI/agentic AI ecosystems and build ML-driven security capabilities across 500+ customer environments. This role spans AI security architecture, MLSecOps, cloud security, detection engineering, and autonomous security operations, and requires deep expertise in security governance and MLOps.

Qualifications

• 10+ years of experience in cybersecurity engineering, software engineering, security architecture, or security data science.
• 3+ years hands-on in AI Security, MLSecOps, or production ML security use cases.
• Strong understanding of GenAI/LLM security, AI agents, RAG, prompt injection, model risk, and AI governance.

Responsibilities

• Define security architecture for GenAI, LLMs, AI agents, RAG pipelines, and MCP integrations.
• Implement agent identity, authorization, permission scoping, behavioral monitoring, and automated containment.
• Establish AI model/SBOM governance, model provenance, dependency security, and supply-chain controls.
• Design controls for prompt injection, data leakage, tenant isolation, PII protection, and AI-specific threats.
• Align AI security practices with NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10, ISO 42001, and ISO 27001.
• Build ML-driven threat detection, anomaly detection, identity risk scoring, and predictive security capabilities.
• Architect autonomous security agents for threat hunting, vulnerability management, configuration auditing, and incident response.
• Integrate LLMs into SOAR, security triage, investigation, and response workflows.
• Use security telemetry to identify emerging attack patterns and improve detection accuracy.
• Design scalable security telemetry pipelines across EDR, SIEM, SOAR, WAF/ZTNA, PAM, cloud, and DevOps environments.
• Develop cross-platform detection and correlation capabilities.
• Embed security and observability requirements into CI/CD through DevSecOps and policy-as-code.
• Secure large-scale AWS, Azure, and GCP environments, including Kubernetes and multi-tenant SaaS architectures.
• Serve as the technical authority for AI Security and MLSecOps.

Skills

Cybersecurity

Security architecture

ML security

Python

Cloud security

Kubernetes

DevSecOps

AI security frameworks

Education

Bachelor's in CS/SE/Cybersecurity

Master's preferred

Security certs a plus

Tools

LangChain

LangGraph

CrewAI

Job description

At o9 Solutions, our mission is to transform enterprise decision-making through an AI-first platform. Global organizations including Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their planning and supply chains.

About the Role

We are looking for a Senior AI Security & MLSecOps Architect to lead the next generation of AI-native security at o9.

This role has two key missions:

• Secure o9's GenAI and agentic AI ecosystem against emerging AI-specific threats.
• Build AI/ML-driven security capabilities that improve threat detection, prediction, and automated response across 500+ customer environments.

You will work across AI security architecture, agent security, RAG security, MLSecOps, cloud security, detection engineering, and autonomous security operations.

What You'll Do

AI Security & Governance

• Define security architecture for GenAI, LLMs, AI agents, RAG pipelines, and MCP integrations.
• Implement agent identity, authorization, permission scoping, behavioral monitoring, and automated containment.
• Establish AI model/SBOM governance, model provenance, dependency security, and supply-chain controls.
• Design controls for prompt injection, data leakage, tenant isolation, PII protection, and AI-specific threats.
• Align AI security practices with NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10, ISO 42001, and ISO 27001.

AI/ML for Security Operations

• Build ML-driven threat detection, anomaly detection, identity risk scoring, and predictive security capabilities.
• Architect autonomous security agents for threat hunting, vulnerability management, configuration auditing, and incident response.
• Integrate LLMs into SOAR, security triage, investigation, and response workflows.
• Use security telemetry to identify emerging attack patterns and improve detection accuracy.

Security Platform & Cloud

• Design scalable security telemetry pipelines across EDR, SIEM, SOAR, WAF/ZTNA, PAM, cloud, and DevOps environments.
• Develop cross-platform detection and correlation capabilities.
• Embed security and observability requirements into CI/CD through DevSecOps and policy-as-code.
• Secure large-scale AWS, Azure, and GCP environments, including Kubernetes and multi-tenant SaaS architectures.

Technical Leadership

• Serve as the technical authority for AI Security and MLSecOps.
• Define architecture standards and security engineering best practices.
• Evaluate emerging AI security technologies and translate research into production capabilities.
• Mentor security and ML engineers across both disciplines.

What You'll Bring

• 10+ years of experience in cybersecurity engineering, software engineering, security architecture, or security data science.
• 3+ years of hands-on experience in AI Security, MLSecOps, or production ML security use cases.
• Strong understanding of GenAI/LLM security, AI agents, RAG, prompt injection, model risk, and AI governance.
• Experience with AI agent frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
• Strong experience with enterprise security platforms such as EDR, SIEM, SOAR, WAF/ZTNA, or PAM.
• Deep cloud and Kubernetes security experience across AWS, Azure, and/or GCP.
• Strong Python experience for security automation, ML development, or data pipelines.
• Experience with ML frameworks such as scikit-learn, XGBoost, or PyTorch.
• Understanding of MITRE ATT&CK, MITRE ATLAS, OWASP LLM Top 10, NIST AI RMF, ISO 42001, and ISO 27001.
• Experience with MLOps/model lifecycle management is a plus.
• Strong architecture, communication, and technical leadership skills.

Education & Certifications

• Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, AI, or a related field.
• Master's degree is a plus.
• Cloud security, CISM, SANS, or other relevant security certifications are a plus.

Why o9?

o9 Solutions is a rapidly growing technology company with a global presence and a $3.7B valuation. Our security organization protects 500+ customer environments across 60+ countries, with large-scale cloud, Kubernetes, and security infrastructure.

This is an opportunity to define how AI security is built and operated at enterprise scale, rather than simply maintaining existing security controls.