Vice President — Principal Applied AI Data Scientist
Company: JPMorganChase
Location: Jersey City
Posted on: April 1, 2026
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Job Description:
Description JPMorgan Chase’s Asset & Wealth Management Finance
organization is advancing the frontier of agentic AI, deploying
digital workers that transform forecasting, analytics, and decision
support. As Vice President, you will lead the design, deployment,
and scaling of large language model (LLM) agents and AI-driven
solutions, driving innovation and business impact across finance
workflows. You will shape strategy, architect robust systems, and
mentor teams to deliver trusted, actionable insights for complex
financial questions. Job responsibilities Define and execute the
roadmap for agentic AI and digital worker solutions in Finance,
aligning with business priorities and emerging technologies.
Identify and prioritize high-value use cases, translating ambiguous
business challenges into measurable outcomes Lead cross-functional
teams, collaborating with Finance, Product, Engineering, and
Operations to deliver scalable, production-grade AI solutions.
Architect, build, and scale LLM agents for finance workflows using
advanced techniques such as LangGraph, retrieval augmented
generation (RAG), multi-agent orchestration, tool use, and
multi-step reasoning Oversee the development of robust data and
inference pipelines in Python and SQL; integrate agents with APIs,
microservices, BI/reporting tools, and cloud platforms (AWS, Azure,
GCP) Leverage vector databases, embeddings, and distributed compute
frameworks (e.g., Databricks, Snowflake, PySpark) for efficient
retrieval and performance optimization. Drive research and
development initiatives, exploring Gen AI, Agentic AI, and
autonomous workflow patterns. Mentor and upskill teams; deliver
enablement materials, documentation, and best practices for AI
adoption. Foster a culture of innovation, experimentation, and
continuous improvement. Translate model outputs into user-friendly
insights and analytics for end users, enabling data-driven decision
making. Communicate complex technical concepts to senior
stakeholders; deliver compelling data visualizations and
narratives. Required qualifications, capabilities and skills 8
years in data/ML roles, including 4 years building and operating
production ML applications; hands?on experience with LLMs. Strong
Python and SQL; Practical knowledge of RAG, prompt engineering,
fine?tuning, function/tool calling, and vector stores. Experience
with cloud platforms (e.g., AWS, Azure, or GCP) and modern data
stacks (e.g., Databricks or Snowflake). Familiarity with LLM
frameworks and orchestration (e.g., LangChain or LlamaIndex) and
REST/GraphQL API design. Proficiency in analytics and applied
statistics; ability to design experiments and evaluate business
impact. Excellent communication and stakeholder management; comfort
working across Finance, Technology, and Operations. Preferred
qualifications, capabilities and skills Experience building
multi?agent systems, autonomous workflows, or task planners.
Knowledge of model safety, bias, and privacy techniques; experience
with model risk management and governance. Exposure to
observability tools (logging, tracing, telemetry) and A/B testing.
Background integrating agents with BI/reporting and workflow tools;
familiarity with Tableau or similar is a plus. Experience with
GPUs/accelerators, containerization, and infrastructure?as?code.
Experience with PySpark or distributed compute. What success looks
like 90 days: deliver a pilot finance agent with RAG and evaluation
metrics, integrated with key data sources and APIs. 6 months: scale
agents across multiple workflows, establish guardrails and
monitoring, and demonstrate clear improvements in cycle time,
accuracy, or user satisfaction.
Keywords: JPMorganChase, Levittown , Vice President — Principal Applied AI Data Scientist, IT / Software / Systems , Jersey City, New York
