Lead Security Engineer - Java, Python, AWS, AIML

Job Description

Take on a crucial role where you'll be a key part of a high-performing team delivering secure software solutions. Make a real impact as you help shape the future of software security at one of the world's largest and most influential companies.

The ideal candidate will have a strong background in AIML Red Teaming, Architecture of Large Language Models (LLM), LLM Security Inference Testing, and a deep understanding of RAG-based systems and equivalents. You will be responsible for identifying vulnerabilities, defining security controls, and engineering the tools to enhance the security posture of our AIML deployments.

• Executes creative security solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions and break down technical problems
• Develops secure and high-quality production code and reviews and debugs code written by others
• Minimizes security vulnerabilities by following industry insights and governmental regulations to continuously evolve security protocols, including creating processes to determine the effectiveness of current controls
• Works with stakeholders and business leaders to understand security needs and recommend business modifications during periods of vulnerability
• Conducts discovery,vulnerability, penetration testing,and threat scenarios onmultiple organizational assets to identifyand assess if vulnerabilities arepresent, and executes threat modeling for multiple applications including external applications interacting with the internal JPMorgan Chase network
• Adds to team culture of diversity, equity, inclusion, and respect

• Formal training or certification on Security engineering concepts and 5+ years applied experience
• Hands on Java and Python development, with hands-on coding experience.
• Experienced with Spring and Spring Boot frameworks.
• Skilled in MySQL and SQL, capable of writing and maintaining stored procedures.
• Knowledgeable in microservices architecture and API security.
• Familiar with cloud computing services, including AWS and Azure.
• Understanding of infrastructure as code (IaC) tools like Terraform and networking protocols such as TCP/IP.

• Familiar in securing AI/ML systems with understanding in AI technologies like Python, TensorFlow, and PyTorch.
• Proficient in the model development lifecycle, including data preparation, model training, testing, and deployment (LLMOps).
• Familiar about AI system threats, attack surfaces, and security controls throughout the MDLC.
• Familiar with AI safety, alignment, cybersecurity concepts, and GenAI security.
• Certifications in cloud security or AI/ML security.
• Familiar in Unix, shell scripting, and container technologies like Docker and Kubernetes.
• Bachelor's or Master's degree in Computer Science, Information Security, or a related field.