Lead AI & Cloud Software Engineer (Java/AWS/ML)

JPMorgan Chase & Co.; Plano (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

JPMorganChase in Plano, TX seeks a Lead Software Engineer to design and build AI-enabled, cloud-native solutions within the Commercial & Community Banking division. You will contribute across the full stack, drive secure coding practices, and orchestrate AI-enabled workflows.

The role combines hands-on Java with AWS ECS/EKS, Postgres, and microservices, while advancing enterprise AI capabilities and reliable delivery within an agile team.

Qualifications

• Formal training or certification in Software Engineering and 5+ years 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 with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
• Influence product design, application functionality, and technical operations within the team and domain by proposing pragmatic architectures, tradeoffs, and standards aligned to firm SDLC, security, and controls expectations.
• Hands-on experience with Large Language Models (LLMs) and generative AI use cases (e.g., RAG, agents, prompt/tool orchestration, evaluation/guardrails).
• Familiarity with AI/ML frameworks and ecosystems such as PyTorch, TensorFlow, scikit-learn, Hugging Face.
• Experience with distributed systems and at least one major cloud platform (AWS, GCP, or Azure).
• Expertise in microservices, RESTful APIs, and data technologies (relational and/or NoSQL).
• Practical experience building cloud-native systems (event-driven architectures, streaming, service mesh, etc.).
• Familiarity with DevOps practices and tools for continuous integration and deployment.

Responsibilities

• Design and develop creative full-stack software solutions using innovative approaches.
• Build and implement AI-driven capabilities, including LLM-based services, orchestration, and integrations into business workflows.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Leverages enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including AI-assisted development and automation capabilities, to improve automation value.
• Architect and deliver cloud-native microservices and APIs (REST/streaming), ensuring scalability, resilience, and strong security controls.
• Identify and automate solutions for recurring operational issues to improve system stability and observability.
• Communicate project status clearly and manage priorities across multiple initiatives.
• Collaborate within a Scrum team, participate in Agile ceremonies, and support a culture of diversity, opportunity, and inclusion.
• Codes in Java, AWS ECS, EKS, and Postgres.
• Utilizes AI agents (CoPilot, Claude) to improve quality and delivery timelines.

Skills

Software engineering

System design

AI-assisted development

Responsible AI

Agile

LLMs

AI/ML frameworks

Distributed systems

Cloud platforms

Microservices

RESTful APIs

DevOps CI/CD

Education

Software Engineering degree

Tools

Docker

Kubernetes

Helm

CI/CD tooling

AWS ECS

EKS

Job description

JPMorganChase in Plano, TX seeks a Lead Software Engineer to design and build AI-enabled, cloud-native solutions within the Commercial & Community Banking division. You will contribute across the full stack, drive secure coding practices, and orchestrate AI-enabled workflows.

The role combines hands-on Java with AWS ECS/EKS, Postgres, and microservices, while advancing enterprise AI capabilities and reliable delivery within an agile team.