Lead Software Engineer Java, Streaming, AWS

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible.

As a Lead Software Engineer at JPMorganChase within the Consumer and Community Banking Credit Card Pricing youare an integral part of an agile team that works to enhance build and deliver trusted market-leading technology products in a secure stable and scalable way. As a core technical contributor you are responsible for conducting critical technology solutions across multiple technical areas within Credit Card Pricing Business domain in support of the firms business objectives.

Job responsibilities

• Executes creative software solutions design development and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Develops secure high-quality production code reviews and debugs code written by others.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
• Adds to team culture of diversity opportunity inclusion and respect.
• Lead design and delivery of cloud-native services using Java 11/17/21 Spring Boot PostgreSQL Kafka and AWS services. Produce secure highquality production-grade code and review PRs for peers.
• Apply design patterns and software design principles (SOLID DRY 12Factor hexagonal/clean architecture) to create maintainable scalable solutions and articulate tradeoffs.
• Build and optimize event-driven architectures with Apache Kafka (topic design producers/consumers schema evolution delivery semantics performance tuning).
• Own service lifecycle and operational stability: CI/CD pipelines automated testing observability (logging/metrics/tracing) incident response reliability and resiliency patterns.
• Partner with product and architecture to align roadmaps APIs and standards; proactively communicate status risks and technical decisions to stakeholders.

Required qualifications capabilities and skills

• Formal training or certification on software engineering concepts and 5 years of applied experience including experience as a Technical Lead
• Hands-on practical experience delivering system design application development testing and operational stability.
• Advanced in one or more programming language(s). Must have deep technical knowledge on Java. Also good working knowledge on Python.
• Advanced understanding of agile methodologies such as CI/CD Application Resiliency and Security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g. cloud artificial intelligence machine learning mobile etc.)
• In-depth knowledge of the financial services industry and their IT systems.
• Practical cloud native experience.
• Strong handson expertise with Java 11/17/21 and Spring Boot; proficiency with build tooling (Maven/Gradle) and dependency management.
• Advanced SQL and relational data modeling with PostgreSQL; performance tuning indexing query plans and schema migration tooling (Flyway/Liquibase).
• Production experience with Apache Kafka (consumer groups partitions idempotence exactlyonce/atleastonce strategies monitoring).

• Practical experience building on AWS (e.g. ECS/EKS/EMR Lambda API Gateway/ALB S3 IAM CloudWatch Parameter Store/Secrets Manager); familiarity with IaC (Terraform/CloudFormation).

  
  
  
  Preferred Qualifications

• Familiarity with how Large Language Models (LLMs) work at a high level including concepts like using agents to break tasks into steps basic planning and reasoning approaches and related techniques.
• General awareness of major LLMs and what theyre good at (e.g. strengths limits typical use cases) without needing deep specialization.
• Experience deploying basic ML or AI-powered services on the cloud preferably AWS.
• Python skills for building data-driven features and simple AI pipelines.