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, Golang 

• 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): Azure Developer Associate, DevOps Engineer Expert 

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