Cisco Systems, Inc.
Overview
Cisco's Security Visibility and Incident Command (SVIC) is looking for an AI/ML Architect to lead the design and strategy for SVIC's innovative AI/ML initiatives. The candidate is expected to architect and guide the development of solutions demonstrating security and vulnerability data and logs processed by the SVIC team, significantly advancing our threat detection mechanisms through innovative anomaly detection and other AI/ML models. The ideal candidate should possess deep expertise in AI/ML architecture, system design, and various domains of information technology, including, but not limited to, software development, data science, data engineering, security, and big-data solutions. The candidate will work independently and lead team members to design, architect, deploy, govern, and support robust and scalable solutions for security event detection, analysis, incident response, investigations, and forensics.
Responsibilities
Designing and implementing scalable, resilient, and high-performance AI/ML architectures for threat detection using security data and telemetry.
Leading the technical vision, strategy, and roadmap for AI/ML solutions within SVIC.
Overseeing the end-to-end lifecycle of AI/ML projects, from conceptualization and architectural design through to deployment, monitoring, MLOps, and continuous improvement.
Guiding the development of advanced anomaly detection AI/ML models and other machine learning solutions.
Establishing guidelines and patterns for developing detections (plays) maximizing Python/notebooks and other relevant technologies.
Employing deep expertise in AI/ML architecture, data engineering, and data science to drive the maturation of Cisco's cybersecurity operations, and enable knowledge sharing and AI/ML learning across teams.
Architecting and overseeing the automation of analytical processes used to identify potentially critical security vulnerabilities, applying data from threat intelligence tools and external, open-source data sources.
Leading the architectural design and implementation of predictive analytics capabilities around threats, vulnerabilities, and security incidents.
Leading collaborations with Cyber Security, Engineering, and Product teams on multi-functional AI/ML initiatives, analytics, and automation.
Defining, establishing, and enforcing standards and guidelines for data quality, data governance, and model management in AI/ML systems.
Providing architectural oversight and guidance on data engineering pipelines and infrastructure required to support AI/ML solutions.
Mentoring and guiding data scientists and ML engineers on AI/ML guidelines, architectural patterns, and new technologies.
Evaluating, prototyping, and recommending new AI/ML technologies, tools, frameworks, and methodologies to enhance SVIC's capabilities.
Ensuring AI/ML solutions align with security, privacy, ethical considerations, and responsible AI principles.
Relevant Technologies
Strong Python development skills and experience with common AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) (required).
Deep knowledge of data science tools, packages, various ML model architectures (e.g., deep learning, NLP, reinforcement learning), and their trade-offs (required).
Tried experience in architecting, developing, and deploying production-grade AI/ML systems at scale (required).
Expertise in designing and deploying AI/ML solutions on cloud platforms (AWS, Google Cloud Platform, Azure), including their AI/ML services (e.g., SageMaker, Vertex AI, Azure ML) (required).
Strong experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, CI/CD for ML) (required).
Proficiency in designing data pipelines, data warehousing solutions (e.g., Snowflake, BigQuery), and working with big data technologies (e.g., Spark, Kafka) for AI/ML.
Splunk Query Language, Scripting using regular expressions (good to have).
Working with security data (e.g., SIEM, EDR, network logs) and knowledge of information security domains (highly desirable).
Job Requirements
BS/MS (PhD preferred) in Computer Science, AI, Machine Learning, Data Science, or a related quantitative field, and 8-10+ years of experience in AI/ML, with at least 3-5 years in an architectural or technical leadership role.
Extensive experience in designing, building, and deploying complex AI/ML models and end-to-end systems in production environments.
Deep understanding of IT infrastructure, software development lifecycle (SDLC), microservices architecture, and cloud-native technologies.
Some experience with a wide variety of security technologies and concepts.
Consistent record of architecting and delivering successful, large-scale AI/ML solutions that have a significant business impact.
Strong problem resolution/analytical skills required to understand and design complex AI/ML system interactions and data flows.
Strong work prioritization, strategic planning, and organizational skills, with experience leading complex technical projects.
Excellent listening, communication (verbal and written), and relationship-building skills, with the ability to articulate complex technical concepts to diverse audiences (both technical and non-technical customers).
Strong documentation skills with meticulous attention to detail, especially for architectural designs and technical specifications.
Strong solving and debugging skills for complex AI/ML systems.
Demonstrated ability to lead projects and provide technical direction to teams with minimal guidance throughout the entire lifecycle of a project.
Additional Qualifications
Relevant certifications in AI/ML, Cloud Architecture (e.g., AWS Certified Solutions Architect - Professional, Google Professional Machine Learning Engineer, Azure AI Engineer Associate), and/or Security (e.g., CISSP).
Experience with Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible) for deploying and handling AI/ML infrastructure.
Publications or presentations in reputable AI/ML or cybersecurity conferences/journals.
About Cisco SVIC Cisco's Security Visibility and Incident Command Team (SVIC) is recognized across the globe as a leader in Information Security and Incident Response operations. Our team of ~100 people comprises industry veterans, renowned security guides and authors, and up‑coming security professionals. We are the investigative branch of Cisco's Security and Trust Organization (S&TO) and provide Cisco with tailored security monitoring and response services to protect against network threats and intellectual asset loss.
Why Cisco
We connect everything — people, process, data, and things — and we use those connections to change our world for the better.
We innovate everywhere — from launching a new era of networking that adapts, learns, and protects, to building Cisco services that accelerate businesses and business results. Our technology powers entertainment, retail, healthcare, education, and more.
We benefit everyone—we do all of this while aspiring for a culture that empowers every person to be the difference, at work and in our communities.
Our Culture At Cisco, we are revolutionizing how data and infrastructure connect and protect organizations in the AI era and beyond. We collaborate with empathy to make big things happen on a global scale, powered by technology that brings people, process, and data together.
#J-18808-Ljbffr
Responsibilities
Designing and implementing scalable, resilient, and high-performance AI/ML architectures for threat detection using security data and telemetry.
Leading the technical vision, strategy, and roadmap for AI/ML solutions within SVIC.
Overseeing the end-to-end lifecycle of AI/ML projects, from conceptualization and architectural design through to deployment, monitoring, MLOps, and continuous improvement.
Guiding the development of advanced anomaly detection AI/ML models and other machine learning solutions.
Establishing guidelines and patterns for developing detections (plays) maximizing Python/notebooks and other relevant technologies.
Employing deep expertise in AI/ML architecture, data engineering, and data science to drive the maturation of Cisco's cybersecurity operations, and enable knowledge sharing and AI/ML learning across teams.
Architecting and overseeing the automation of analytical processes used to identify potentially critical security vulnerabilities, applying data from threat intelligence tools and external, open-source data sources.
Leading the architectural design and implementation of predictive analytics capabilities around threats, vulnerabilities, and security incidents.
Leading collaborations with Cyber Security, Engineering, and Product teams on multi-functional AI/ML initiatives, analytics, and automation.
Defining, establishing, and enforcing standards and guidelines for data quality, data governance, and model management in AI/ML systems.
Providing architectural oversight and guidance on data engineering pipelines and infrastructure required to support AI/ML solutions.
Mentoring and guiding data scientists and ML engineers on AI/ML guidelines, architectural patterns, and new technologies.
Evaluating, prototyping, and recommending new AI/ML technologies, tools, frameworks, and methodologies to enhance SVIC's capabilities.
Ensuring AI/ML solutions align with security, privacy, ethical considerations, and responsible AI principles.
Relevant Technologies
Strong Python development skills and experience with common AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) (required).
Deep knowledge of data science tools, packages, various ML model architectures (e.g., deep learning, NLP, reinforcement learning), and their trade-offs (required).
Tried experience in architecting, developing, and deploying production-grade AI/ML systems at scale (required).
Expertise in designing and deploying AI/ML solutions on cloud platforms (AWS, Google Cloud Platform, Azure), including their AI/ML services (e.g., SageMaker, Vertex AI, Azure ML) (required).
Strong experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, CI/CD for ML) (required).
Proficiency in designing data pipelines, data warehousing solutions (e.g., Snowflake, BigQuery), and working with big data technologies (e.g., Spark, Kafka) for AI/ML.
Splunk Query Language, Scripting using regular expressions (good to have).
Working with security data (e.g., SIEM, EDR, network logs) and knowledge of information security domains (highly desirable).
Job Requirements
BS/MS (PhD preferred) in Computer Science, AI, Machine Learning, Data Science, or a related quantitative field, and 8-10+ years of experience in AI/ML, with at least 3-5 years in an architectural or technical leadership role.
Extensive experience in designing, building, and deploying complex AI/ML models and end-to-end systems in production environments.
Deep understanding of IT infrastructure, software development lifecycle (SDLC), microservices architecture, and cloud-native technologies.
Some experience with a wide variety of security technologies and concepts.
Consistent record of architecting and delivering successful, large-scale AI/ML solutions that have a significant business impact.
Strong problem resolution/analytical skills required to understand and design complex AI/ML system interactions and data flows.
Strong work prioritization, strategic planning, and organizational skills, with experience leading complex technical projects.
Excellent listening, communication (verbal and written), and relationship-building skills, with the ability to articulate complex technical concepts to diverse audiences (both technical and non-technical customers).
Strong documentation skills with meticulous attention to detail, especially for architectural designs and technical specifications.
Strong solving and debugging skills for complex AI/ML systems.
Demonstrated ability to lead projects and provide technical direction to teams with minimal guidance throughout the entire lifecycle of a project.
Additional Qualifications
Relevant certifications in AI/ML, Cloud Architecture (e.g., AWS Certified Solutions Architect - Professional, Google Professional Machine Learning Engineer, Azure AI Engineer Associate), and/or Security (e.g., CISSP).
Experience with Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible) for deploying and handling AI/ML infrastructure.
Publications or presentations in reputable AI/ML or cybersecurity conferences/journals.
About Cisco SVIC Cisco's Security Visibility and Incident Command Team (SVIC) is recognized across the globe as a leader in Information Security and Incident Response operations. Our team of ~100 people comprises industry veterans, renowned security guides and authors, and up‑coming security professionals. We are the investigative branch of Cisco's Security and Trust Organization (S&TO) and provide Cisco with tailored security monitoring and response services to protect against network threats and intellectual asset loss.
Why Cisco
We connect everything — people, process, data, and things — and we use those connections to change our world for the better.
We innovate everywhere — from launching a new era of networking that adapts, learns, and protects, to building Cisco services that accelerate businesses and business results. Our technology powers entertainment, retail, healthcare, education, and more.
We benefit everyone—we do all of this while aspiring for a culture that empowers every person to be the difference, at work and in our communities.
Our Culture At Cisco, we are revolutionizing how data and infrastructure connect and protect organizations in the AI era and beyond. We collaborate with empathy to make big things happen on a global scale, powered by technology that brings people, process, and data together.
#J-18808-Ljbffr