JPMorgan Chase—Associate - Data Science / Applied AI ML

Job description

Description: Job Responsibilities - Develop AI-powered applications leveraging LLMs, Generative AI, Agentic AI, and advanced analytics. - Build and enhance AI agents that interact with enterprise tools, data sources, APIs, and business workflows. - Develop orchestration workflows using frameworks such as LangGraph, Semantic Kernel, LangChain, or similar technologies. - Implement MCP (Model Context Protocol) integrations to securely connect AI applications with enterprise systems, knowledge sources, and services. - Build and support Retrieval-Augmented Generation (RAG), GraphRAG, and Knowledge Graph solutions. - Develop scalable Python-based applications, APIs, and services to support AI and analytics use cases. - Integrate enterprise LLM platforms and GenAI services into business workflows and operational processes. - Perform data exploration, experimentation, testing, and performance optimization across structured and unstructured datasets. - Create dashboards, reporting solutions, and user-facing applications that translate AI outputs into actionable insights. - Collaborate with Compliance, Technology, and Business stakeholders to understand requirements and deliver high-quality solutions. - Contribute to reusable frameworks, engineering standards, testing practices, and AI governance requirements. Required Qualifications and Skills - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative discipline. - 5+ years of experience developing software, automation, analytics, or AI solutions. - Strong programming skills in Python and SQL. - Experience working with LLMs, Generative AI platforms, prompt engineering, and AI application development. - Experience building solutions using orchestration frameworks such as LangGraph, LangChain or similar technologies. - Understanding of Agentic AI concepts, tool calling, workflow automation, memory management, and multi-step reasoning. - Experience implementing MCP (Model Context Protocol) integrations or similar enterprise integration patterns. - Familiarity with RAG, embeddings, vector databases, semantic search, and knowledge retrieval techniques. - Experience working with REST APIs, JSON, and enterprise system integrations. - Strong problem-solving, analytical, and communication skills. - Ability to work independently and collaboratively in a fast-paced environment. Preferred Qualifications - Experience with Neo4j, Knowledge Graphs, or GraphRAG architectures. - Experience with AI observability, evaluation frameworks, and LLM testing methodologies. - Experience with cloud-based AI platforms and enterprise AI ecosystems. - Familiarity with compliance, risk management, or financial services domains. - Experience building AI copilots, assistants, workflow automation solutions, or multi-agent systems.