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 Lang Graph.
• 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 Lang Graph 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