JPMorgan Senior Lead Security Engineer – AI 

United States, Virginia 

869102866

You will also have a working knowledge of how to improve the quality of responses from LLMs, in addition to in-depth knowledge of serving private models in an Enterprise setting.

Job Responsibilities:

• Work with Cybersecurity domain experts to develop or reuse Machine Learning and AI models that achieve Cybersecurity outcomes.
• Demonstrate working knowledge of vector databases, agents, and tools to support AI applications such as Retrieval Augmented Generation (RAG).
• Develop solutions using privately hosted LLMs, ensuring scalability, reliability, and efficient GPU utilization.
• Create solutions using LLMs and traditional NLP for Text Clustering, Classification, and Feature Extraction.
• Apply working knowledge of prompt engineering and dataset curation for optimizing LLM performance.
• Evaluate and assess model and overall solution performance.
• Execute creative security solutions, design, development, and technical troubleshooting, thinking beyond routine approaches.
• Develop secure and high-quality production code, reviewing and debugging code written by others.
• Minimize security vulnerabilities by following industry insights and governmental regulations, continuously evolving security protocols.
• Collaborate with stakeholders and business leaders to understand security needs and recommend business modifications during periods of vulnerability.
• Contribute to a team culture of diversity, equity, inclusion, and respect.

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on Data Science concepts and 5+ years applied experience.
• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, or Computer Science.
• Exceptional understanding of Deep Learning models and Transformer architectures.
• Proficiency in Deep Learning frameworks such as TensorFlow, PyTorch, or Keras.
• Experience with RAG frameworks like Langchain or Llamaindex.
• Familiarity with GPU-enabled platforms, monitoring tools, and performance optimization strategies.
• Experience with Amazon Web Services and OpenAI.
• Working knowledge of Responsible AI, model fairness, and reliability and safety.
• Advanced proficiency in one or more programming languages.
• Proficient in all aspects of the Software Development Life Cycle, advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Skilled in planning, designing, and implementing enterprise-level security solutions.

Preferred Qualifications, Capabilities, and Skills:

• Experience effectively communicating with senior business leaders.
• Expertise in cloud platforms (e.g., AWS, GCP, Azure) related to AI model deployments. Certifications in one or more cloud platforms are a plus.
• Experience integrating or deploying LLM models in production environments.
• Experience with fine-tuning LLMs is a plus.
• Experience with AWS OpenSearch, Graph Databases, and developing REST APIs using Flask or FastAPI is a plus.