Lead Software Engineer - Fullstack Java/AWS/AI/ML

Lead Software Engineer - Fullstack Java/AWS/AI/ML at JPMorganChase in Plano, TX (onsite) focused on delivering secure, scalable technology across frontend, backend, AI/ML, and data pipelines.

Responsibilities

• Design, implement, and troubleshoot innovative software solutions as a core contributor on an agile team, approaching problems beyond conventional methods to deliver effective outcomes.
• Champion enterprise AI assisted engineering practices to elevate code quality, delivery speed, and operational outcomes, including AI assisted code review, refactoring, test strategy acceleration, and incident analysis support; establish consistent validation standards (secure coding, peer review, automated testing) and promote reusable patterns.
• Leverage SDLC tools, including AI assisted development and automation capabilities, to maximize the value delivered by automation.
• Full stack development: build modern frontend applications with JavaScript frameworks (React, Angular, or Vue.js), develop robust backend services in Java and Python, and ensure seamless integration across UI layers, APIs, middleware, and data stores.
• AI/ML model development and edge deployment: train, fine tune, and optimize models using PyTorch, TensorFlow, Hugging Face, ONNX, and TensorRT; package for edge device inference and cloud backends; manage the full lifecycle from experimentation to monitoring.
• Cloud infrastructure and operations on AWS: provision and manage cloud resources for data pipelines and model serving using EC2, S3, Lambda, ECS/EKS, SageMaker, Kinesis, IAM, CloudWatch; uphold operational excellence through monitoring, alerts, cost optimization, and infrastructure as code.
• Data pipeline development and integration: design scalable, fault tolerant pipelines to ingest, transform, and deliver data across distributed systems; architect event driven and streaming data flows with Apache Kafka and other messaging systems to support real time processing.
• Collaboration and technical leadership: partner with data scientists, product managers, and platform teams to translate business requirements into technical solutions; participate in architecture and code reviews and contribute to engineering best practices and standards.

Requirements

• Formal training or certification in software engineering concepts plus 5+ years of applied experience.
• Proven experience leading effective use of approved AI assisted software development tools, with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.
• Programming languages and frameworks: proficiency in JavaScript/TypeScript (with modern front end frameworks), Java (Spring Boot or similar), and Python; demonstrated ability to work across all three ecosystems.
• Data streaming and messaging: extensive experience with Kafka (producers, consumers, Kafka Streams, Connect, Schema Registry) and familiarity with RabbitMQ, AWS SQS/SNS.
• AI/ML model development: hands on experience building and training models with PyTorch, TensorFlow, or JAX; familiarity with model optimization and edge deployment tools (ONNX Runtime, TensorRT, TFLite, Core ML); experience with experiment tracking tools such as MLflow or Weights & Biases.
• AWS cloud operations: hands-on experience operating production workloads on AWS, including provisioning infrastructure, managing deployments, troubleshooting issues, and implementing CI/CD pipelines in a cloud native environment.
• Data engineering: experience building ETL/ELT pipelines and working with structured and unstructured data at scale; familiarity with Apache Spark, Airflow, or Step Functions is a plus.
• Software engineering practices: solid foundation in Git version control, containerization, orchestration, automated testing, and CI/CD tooling.

Technologies

• Java, JavaScript, TypeScript
• React, Angular, Vue.js
• Python
• Java Spring Boot or similar
• PyTorch, TensorFlow, Hugging Face, ONNX, TensorRT
• MLflow, Weights & Biases
• Apache Kafka, RabbitMQ
• AWS: EC2, S3, Lambda, ECS, EKS, SageMaker, Kinesis, IAM, CloudWatch
• SQS, SNS
• JAX, Core ML, TFLite, ONNX Runtime
• Apache Spark, Airflow, Step Functions
• Git, Docker, Kubernetes, Terraform, CloudFormation
• CI/CD tooling

Benefits

• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching
• Commission-based pay and or discretionary incentive compensation (cash and or forfeitable equity)