Lead Security Engineer – AI / ML Laboratory Technical Application Owner

As a Senior Lead Security Engineer at JPMorganChase within the Cybersecurity and Technology Controls line of business, you are an integral part of an agile team that works to deliver software solutions that satisfy pre-defined functional and user requirements with the added dimension of preventing misuse, circumvention, and malicious behavior. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of cybersecurity challenges that span multiple technology domains.

Job responsibilities

• Facilitates security requirements clarification for multiple networks to enable multi-level security to satisfy organizational needs
• Works with stakeholders and senior business leaders to recommend business modifications during periods of vulnerability
• Be responsible for triaging based on risk assessments of various threats and managing resources to cover impact of disruptive events 
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Oversees the integration and functionality of the platform with AWS services. Ensuring the platform supports the full ML lifecycle, including data preparation, model training, testing, and deployment.
• Ensuries that the platform adheres to JP Morgan Chase's data protection policies and AWS security best practices. Implementing access controls and encryption to safeguard sensitive data and models.
• Monitors the performance of ML models and the platform's infrastructure on AWS. Optimizing resource usage and scaling capabilities to handle varying workloads efficiently.
• Collaborates with data scientists, developers, and business units to understand requirements and provide updates on platform capabilities. Facilitating training sessions and support for users of the platform.
• Identifies risks related to model accuracy, data privacy, and cloud service disruptions.  Implementing strategies to mitigate risks, such as regular model evaluations and backup solutions.
• Guides new users through sandbox setup and access; Access Management: Manage secure user permissions and access; Experiment Support: Assist with running and troubleshooting experiments; Results Analysis: Help close experiments and analyze outcomes; Decision Facilitation: Lead result reviews and support go/no-go decisions and readouts with leadership; Continuous Engagement: Maintain user communication for feedback and improvements

Required qualifications, capabilities, and skills

• Formal training or certification on Security Engineering concepts and 3+ years applied experience
• Skilled in planning, designing, and implementing enterprise-level security solutions
• Advanced in one or more programming languages
• Advanced knowledge of software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Extensive experience with threat modeling, discovery, vulnerability, and penetration testing
• Ability to tackle design and functionality problems independently with little to no oversight 
• Proficiency in AWS services, including EC2, S3, Lambda, SageMaker, and other relevant tools for ML model deployment. Strong understanding of machine learning concepts and workflows. Strong experience in terraform.
• Ability to write and maintain scripts for automation and patch deployment. Familiarity with programming languages such as Python, Java, or others used in ML and cloud environments.
• Experience in managing cloud-based infrastructure and applications.  Knowledge of system monitoring tools and techniques.
• Understanding of cybersecurity principles and practices, especially in cloud environments.  Ability to implement security patches and ensure compliance with industry standards.
• Ability to diagnose and resolve technical issues related to the platform and its integration with AWS.  Strong analytical skills to assess the impact of patches and updates.
• Skills in managing projects related to patch creation and deployment.  Ability to coordinate with cross-functional teams and manage timelines effectively.