Lead Security Engineer

Description

As a Lead AIML Security Engineer at JPMorgan Chase, you are an integral part of a team that works to develop and deliver software solutions that satisfy functional and user requirements with the added dimension of preventing misuse, circumvention, and malicious behavior.

Job responsibilities

- Develops secure high-quality production code, and reviews and debugs code written by others

- Develops AIML technical controls software solutions: design, development, and technical troubleshooting across multiple cloud platforms (AWS, Azure, GCP), with the ability to think beyond routine or conventional approaches to building solutions or breaking down technical problems

- Produces technical design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development

- Leads AI Security product evaluations with external vendors, startups, and internal teams to drive outcomes-oriented probing of designs, technical capabilities, and applicability for use within information system

- Contributes to software engineering communities of practice and events that explore new and emerging technologies

- Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

- Advanced in one or more programming language(s): Python, Java

- Proficient in all aspects of the Software Development Life Cycle

- Formal training on software engineering concepts and 5+ years applied development/coding experience

- Proficient in cloud infrastructure-as-code (IaC) tools like Terraform

- Knowledgeable in containers and container orchestration technologies such as Docker, Kubernetes, and Helm

- Extensive practical experience with at least one public cloud (Google Cloud Platform, Amazon Web Services)

- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

- Hands on practical experience in design, application development, testing, and operational stability across AWS, Azure, and GCP

- Practical experience in AI and machine learning technologies

- Knowledgeable in AI safety, AI alignment, AI cybersecurity concepts, and trends, including GenAI security

- Ability to tackle design and functionality problems independently with little to no oversight

Preferred qualifications, capabilities, and skills

- AWS cloud certification(s): AWS Certified Developer – Associate, AWS Certified DevOps Engineer – Professional

- Microsoft cloud certification(s): Microsoft Certified Developer Associates, DevOps Engineer Expert

- Google cloud certification(s): Professional Cloud Developer, Profession DevOps Engineer