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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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Lead Software Engineer - Java, Python, AI/LLM serves as a core technical contributor within the Consumer & Community Banking team. This role involves designing and developing full-stack software solutions, building AI-driven capabilities like LLM-based services and orchestration, and implementing cloud-native microservices and RESTful APIs. The engineer will drive the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational stability while ensuring secure coding standards. Key technical requirements include proficiency in Java, Python, AWS ECS, EKS, and Postgres, alongside experience with PyTorch, TensorFlow, scikit-learn, and Hugging Face. The role focuses on solving complex problems related to scalable system design, automated observability, and the integration of generative AI use cases like RAG and agentic workflows within a secure, stable production environment for market-leading technology products.
Design and develop full-stack software solutions using innovative technical approaches.
Build and implement AI-driven capabilities, including LLM-based services and orchestration into business workflows.
Integrate enterprise-authorized AI tools to accelerate code generation, refactoring, and automated testing.
Architect and deliver cloud-native microservices and APIs ensuring scalability, resilience, and security.
Automate solutions for recurring operational issues to improve system stability and observability.
Establish validation standards for AI-generated outputs to ensure secure coding and performance.
Lead the adoption of AI-assisted engineering practices to improve team delivery speed and code quality.
Develop high-quality software using Java, AWS (ECS/EKS), and Postgres.
What we're looking for
Formal training or certification in Software Engineering and 5+ years of applied experience.
Strong system design, application development, and operational stability skills in production environments.
Hands-on experience using enterprise-authorized AI-assisted software development tools to create, validate, and refine outputs for security and performance.
Experience with Large Language Models (LLMs) and generative AI use cases including RAG, agents, and prompt orchestration.
Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face.
Expertise in microservices, RESTful APIs, and data technologies (relational and/or NoSQL).
Experience building cloud-native systems using distributed architectures, streaming, and at least one major cloud platform.
Advanced Java proficiency; Python knowledge, cloud certifications, and experience with Docker or Kubernetes are preferred.