Lead Machine Learning Engineer – Agentic AI, Vice President

Lead Machine Learning Engineer – Agentic AI, Vice President

Join to apply for the Lead Machine Learning Engineer – Agentic AI, Vice President role at JPMorgan Chase

$/yr - $/yr

Are you passionate about building the next generation of AI solutions? Join us to lead and mentor a team of talented engineers, drive innovation in generative and agentic AI, and deliver impactful, scalable technology for Risk Technology. You’ll collaborate with cross-functional partners and play a key role in shaping the future of Asset and Wealth Management Risk. As a Lead Machine Learning Engineer – Agentic AI in Risk Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects.

You will leverage your expertise in software engineering and multi‑agent system design to deliver complex, high‑impact initiatives. You will mentor and guide a team of engineers, foster best practices in ML engineering, and partner with data science, product, and business teams to deliver end‑to‑end solutions that drive value for the Risk business.

• Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions for the Risk business.
• Design and execute enterprise‑wide, reusable AI/ML frameworks and core infrastructure to accelerate AI solution development.
• Develop multi-agent systems for orchestration, agent‑to‑agent communication, memory, telemetry, and guardrails.
• Guide research on context and prompt engineering techniques to improve prompt‑based model performance, utilizing libraries such as Smart
  
  SDK and Lang Graph.
• Develop and maintain tools and frameworks for prompt‑based agent evaluation, monitoring, and optimization at enterprise scale.
• Build and maintain data pipelines and processing workflows for scalable, efficient data consumption.
• Write secure, high‑quality production code and conduct code reviews.
• Partner with Data Science, Product, and Business teams to identify requirements and develop solutions.
• Communicate technical concepts and results to both technical and non‑technical stakeholders, including senior leadership.
• Provide technical leadership, mentorship, and guidance to junior engineers, promoting a culture of excellence and continuous learning.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 10+ years of experience in machine learning engineering.
• Strong proficiency in Python and experience deploying end‑to‑end pipelines on AWS.
• Hands‑on experience in system design, application development, testing, and operational stability.
• Experience using Lang Graph or Smart
  
  SDK for multi‑agent orchestration.
• Experience with AWS and infrastructure‑as‑code tools such as Terraform.

• Strategic thinker with the ability to drive technical vision for business impact.
• Demonstrated leadership working 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.
• Hands‑on experience building and maintaining user interfaces.

JPMorgan

Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility.…