Your seniority as a security engineer puts you in the ranks of the top talent in your field. Play a critical role at one of the world's most iconic financial institutions where security is vital.
As a Security Engineer III - AI/ML at JPMorgan Chase within the Cybersecurity Technology & Controls, you serve as a seasoned member of a team that works to deliver cutting edge machine learning and AI solutions. You will work on scalable backend systems, real-time prediction models, and advanced automation flows, driving measurable business impact across multiple domains. You will also ensure that AI models and workflows adhere to cybersecurity best practices in support of the firm’s business objectives.
Job Responsibilities
- Lead the end-to end design, development, and deployment of machine learning models and platforms, including LLMs, GANs, and recommendation engines.
- Design, develop, and fine-tune AI/ML models for real-time user behavior prediction, churn reduction, and customer experience automation.
- Uses enterprise-authorized AI capabilities within the work environment to accelerate security analysis and vulnerability assessment documentation, validating outputs and ensuring sensitive data is handled appropriately.
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Applies approved tools to analyze and correlate incident data to identify, interpret, and summarize probability and impact of threats when determining specific vulnerabilities
- Leads delivery of continuity-related awareness, training and educational activities, and exercises
- Applies reuse-first, AI-assisted practices within SDLC/toolchain routines to strengthen security testing and control validation, ensuring traceability/auditability and alignment to resiliency and security expectations.
- Apply RAG concepts, prompt engineering, anomaly detection, and changepoint detection to solve complex business problems.
- Develop and maintain scalable cloud-native applications on AWS, Azure, or Google Cloud.
- Build robust and scalable APIs for integrating machine learning models and backend systems.
- Implement cybersecurity controls to safeguard AI workflows and ensure compliance.
Required Skills
- Formal training or certification and 3+ years of experience with AI models and workflows
- Advanced proficiency in Python and relevant libraries (Pandas, NumPy).
- Hands-on experience with frameworks and libraries including TensorFlow, PyTorch, BERT/LLMs, Hugging Face, OpenCV, scikit-learn, SKLearn, Pandas, Flask and React.
- Expertise in cloud and DevOps technologies, including AWS, Google Cloud, Azure, Docker, Kubernetes, Jenkins, and GitLab.
- Skilled in working with databases such as MySQL, MongoDB, PostgreSQL, and NoSQL systems.
- Strong background in data science and AI, covering deep learning, NLP, GenAI, RAG concepts, prompt engineering, and data visualization.
- Experience in secure coding, model validation, and data privacy.
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support security engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted code/security recommendations before use, escalating when uncertain and following security and data handling requirements.
- Excellent problem-solving, communication, and teamwork skills.
Preferred qualifications, capabilities, and skills
- Experience with LLM fine-tuning, prompt engineering, and multi-modal AI integration.
- Familiarity with CI/CD pipelines and automation tools.
- Knowledge of frontend frameworks (React, Next.js).
- Certifications in AI/ML, Kubernetes, AWS, or cybersecurity.
- Exposure to cybersecurity frameworks and compliance standards.