Lead Software Engineer – AI/ML, Java & AWS Cloud

Aumni; Plano (TX); Presencial; USD 150 000 - 210 000; Tempo integral

Resumo da oferta

JPMorganChase is seeking a Lead Software Engineer to advance trusted, scalable technology in Commercial & Community Banking. You will drive full‑stack development, architect cloud-native microservices, and push AI-enabled capabilities across the SDLC with robust security, testing, and governance.

The role requires strong design, production experience, and hands-on work with LLMs, PyTorch/TensorFlow, and enterprise AI tools.

Qualificações

• Formally trained in Software Engineering with 5+ years of applied experience.
• Strong system design and production-grade development skills.
• Hands-on with enterprise AI-assisted software development tools and evaluating AI outputs.

Responsabilidades

• Design and develop full-stack software solutions with modern approaches.
• Build and implement AI-driven capabilities, including LLM-based services and integrations.
• Promote enterprise AI engineering practices for quality, speed, and security.
• Leverage AI coding assist tools to improve quality and productivity.
• Architect and deliver cloud-native microservices and APIs (REST/streaming).
• Automate recurring issues to improve stability and observability.
• Communicate status and priorities across multiple initiatives.
• Collaborate in a Scrum team and foster inclusion.

Conhecimentos

Software engineering

System design

AI-assisted development

LLMs and generative AI

Distributed systems

Cloud platforms

Microservices

RESTful APIs

DevOps

Secure coding

Formação académica

Bachelor's degree in Computer Science

Software Engineering certification

Ferramentas

AWS ECS

EKS

Postgres

Docker

Kubernetes

Helm

PyTorch

TensorFlow

scikit-learn

Hugging Face

Descrição da oferta de emprego

JPMorganChase is seeking a Lead Software Engineer to advance trusted, scalable technology in Commercial & Community Banking. You will drive full‑stack development, architect cloud-native microservices, and push AI-enabled capabilities across the SDLC with robust security, testing, and governance.

The role requires strong design, production experience, and hands-on work with LLMs, PyTorch/TensorFlow, and enterprise AI tools.