We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Machine Learning Engineer, Agentic AI within Risk Technology at JPMorgan Chase, you will lead a specialized technical area, driving impact across teams, technologies, and projects. In this role, you will leverage your deep knowledge of software engineering, multi-agent system design and leadership to spearhead the delivery of complex and groundbreaking initiatives that will transform Asset and Wealth Management Risk.
You will be responsible for hands-on development, and leading and mentoring of a team of Machine Learning and Software Engineers, focusing on best practices in ML engineering, with the goal of elevating team performance to produce high-quality, scalable systems. You will also engage and partner with data science, product and business teams to deliver end-to-end solutions that will drive value for the Risk business.
Responsibilities:
Lead the deployment and scaling of advanced generative AI, Agentic AI and classical ML solutions for the Risk Business. Lead design and execution of enterprise-wide reusable AI/ML frameworks and core infrastructure capabilities that will accelerate development of AI solutions. Develop multi-agent systems that provide capabilities for orchestration, agent-to-agent communication, memory, telemetry, guardrails, etc. Conduct and guide research on context and prompt engineering techniques to improve the performance of prompt-based models, exploring and utilizing Agentic AI libraries like JPMC’s SmartSDK and LangGraph. Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring and optimization to ensure high reliability at enterprise scale. Build and maintain data pipelines and data processing workflows for scalable and efficient consumption of data. Develop secure, high-quality production code, and provide code reviews. Foster productive partnership with Data Science, Product and Business teams to identify requirements and develop solutions to meet business needs. Communicate effectively with both technical and non-technical stakeholders, including senior leadership. Provide technical leadership, mentorship and guidance to junior engineers, promoting a culture of excellence, continuous learning, and professional growth.
Required qualifications, capabilities and skills:
Bachelor’s degree or Master’s in Computer Science, Engineering, Data Science, or related field Applied experience in Machine Learning Engineering. Strong proficiency in Python and experience deploying end-to-end pipelines on AWS. Hands-on practical experience delivering system design, application development, testing, and operational stability Hands-on experience using LangGraph or JPMC’s SmartSDK for multi-agent orchestration. Experience with AWS and Infrastructure-as-code tools like Terraform.
Preferred Qualifications:
Strategic thinker with the ability to drive technical vision for business impact. Demonstrated leadership working effectively with engineers, data scientists, and ML practitioners. Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines. Experience with Agentic telemetry and evaluation services. Demonstrated hands-on experience building and maintaining user interfaces
