Join a team where you can play a crucial role in shaping the future of a world-renowned company and make a direct and meaningful impact in a space designed for top performers.

As a Senior Lead Security Engineer at JPMorgan Chase within the Cybersecurity and Technology Controls organization, you are an integral part of an agile team that works to deliver software solutions that satisfy pre-defined functional and user requirements with the added dimension of preventing misuse, circumvention, and malicious behavior. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of cybersecurity challenges that span multiple technology domains.

 

Job responsibilities

Create bespoke data models and algorithms tailored to address Cyber Technology Group's requirements and apply them to data sets while developing and employing the company's A/B testing framework to assess model quality  Apply advanced principles, theories, and concepts in the realm of Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), Deep Learning (DL), Generative AI, Transfer Learning, and Reinforcement Learning algorithms to cyber data sets  Utilize open-source and third-party models while contributing to the development of innovative AI capabilities  Coordinate with various functional teams to implement models and track results  Establish processes and tools for monitoring model performance and data accuracy and develop custom models when suitable models are unavailable in JPMC's inventory, from suppliers, or in the open-source domain. Extract and analyze data from JPMC data sources, evaluating the effectiveness and precision of new data sources and data collection techniques  Assess and choose suitable LLM tools and models for diverse tasks including but not limited to curating custom datasets and fine-tune LLM with a focus on parameter-efficient, mixture-of-expert, and instruction methods designing and developing advanced LLM prompts, Retrieval-Augmented Generation (RAG) solutions, and Intelligent agents for the LLMs and executing experiments to push the capability limits of LLM models and enhance their dependability  Orchestrate multiple models and develop innovative approaches for sparse-data situations  Facilitates security requirements clarification for multiple networks to enable multi-level security to satisfy organizational needs Works with stakeholders and senior business leaders to recommend business modifications during periods of vulnerability Triages based on risk assessments of various threats and managing resources to cover impact of disruptive events Adds to a team culture of diversity, equity, inclusion, and respect

 

Required qualifications, capabilities, and skills

Formal training or certification on security engineering concepts and 5+ years applied experience Experience developing ML pipelines, including data gathering from system records, data preparation (analysis and preprocessing), model selection, training, testing, validation, and prediction Proficient in using algorithms such as Linear Regression, Logistic Regression, Decision Tree, Random Forest, Bagging and Boosting, K-Nearest Neighbor, Support Vector Machine, Single/Multi-Layer Perceptron, Feed Forward, CNN, RNN, LSTM, GRU, BERT, Hugging Face and Spacy Models, Naive Bayes, Markov-Model, Graph Models, and more Experience in backend development, including databases (SQL/NoSQL/Graph), programming languages (Python/Java/Node.js), web frameworks, APIs, and microservices and possess front-end development skills, including HTML, CSS, and JavaScript  Familiarity with frameworks such as React or Angular Demonstrate a solid understanding of statistical theory, data mining, or machine learning algorithms. Understand advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and have experience applying them Expertise in Python, SQL, and Spark for developing large-scale applications using extensive datasets and have experience working with and creating data architectures Skilled in planning, designing, and implementing enterprise-level security solutions Advanced knowledge of software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Practical cloud native experience

 

Preferred qualifications, capabilities, and skills

Experience in managing GPU and compute resources in frameworks like PyTorch or TensorFlow  Proficiency in coding with multiple languages, including C, C++, and object-oriented languages  Experience in developing applications in cloud environments such as AWS, Google Cloud, and Azure and familiarity with CI/CD pipelines and Agile methodology Experience utilizing web services such as Redshift, S3, Spark, DigitalOcean, etc. Familiarity with distributed data/computing tools like Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, and others Experience in  LLM based solution development and wrapper languages; e.g., OpenAI with LangChain and intelligent Agents Show proven experience in applying AI to comprehensive and practical technology solutions