Lead Machine Learning Engineer Agentic AI, Vice President

JPMorgan Chase-posted 3 days ago
Full-time • Mid Level
Jersey City, NJ
5,001-10,000 employees
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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 SmartSDK and LangGraph.
  • 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 LangGraph or SmartSDK 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.
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