Aws Senior Lead Software Engineer- Java / Python

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Consumer & Community Banking

Senior Lead Software Engineer with Java/Python expertise on AWS, focusing on designing, developing, and troubleshooting complex software solutions. The role involves working with AWS services, data lake architectures, and has exposure to AI/ML concepts like model inference and deployment.

What you'd actually do

  1. Execute end-to-end software solutions — including design, development, and technical troubleshooting — with the ability to think beyond routine or conventional approaches to solve complex technical problems
  2. Develop secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems
  3. Produce architecture and design artifacts for complex applications while ensuring design constraints are met throughout the software development process
  4. Gather, analyze, synthesize, and visualize data from large, diverse data sets to drive continuous improvement of software applications and systems
  5. Proactively identify hidden problems and patterns in data, leveraging these insights to drive improvements in coding hygiene and system architecture

Skills

Required

  • software engineering concepts
  • system design
  • application development
  • testing
  • operational stability
  • SQL
  • Java
  • springboot
  • microservices
  • Python API development
  • AWS
  • AWS infrastructure
  • AWS services
  • SageMaker
  • Bedrock
  • EMR
  • Glue
  • Spark
  • data lake architectures
  • Snowflake
  • Databricks
  • AI/ML concepts
  • model inference
  • model evaluation
  • model deployment
  • automation
  • continuous delivery
  • cloud
  • artificial intelligence
  • machine learning
  • mobile
  • Computer Science
  • Computer Engineering
  • Mathematics

Nice to have

  • building or integrating applications powered by large language models (LLMs)
  • retrieval-augmented generation (RAG)
  • generative AI techniques
  • TensorFlow
  • PyTorch
  • scikit-learn
  • MLOps practices
  • model versioning
  • model monitoring
  • automated retraining pipelines

What the JD emphasized

  • Advanced proficiency in SQL and one or more programming languages including Java, springboot, microservices, or Python API development
  • Strong experience designing and implementing solutions on AWS including hands-on experience with AWS infrastructure and services such as Step Functions, S3, SQS, Lambda, and AI/ML services such as SageMaker and Bedrock and AWS data processing and transformation services such as EMR, Glue, and Spark
  • Exposure to AI/ML concepts, including model inference, evaluation, and deployment in production environments