Example Company
Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
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Lead Software Engineer
- Location
- Chicago
- Type
- Full time
- Posted
- 5D AGO
About the role
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorganChase within the Consumer Community Banking Digital Technology department, you are 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 various business functions in support of the firm’s business objectives.
Job responsibilities
As a Lead Software Engineer at JPMorganChase within the Consumer Community Banking Digital Technology department, you are 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 various business functions in support of the firm’s business objectives.
Job responsibilities
- Design, development and deliver software solutions with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Perform troubleshooting and performance tuning across backend workflows (Java, Spring Boot, AWS, PostgreSQL)
- Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems
- Develop, support and troubleshoot cloud, big data and java solutions required to fulfill business and technology requirements
- Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Gather, analyze, synthesize, and develop visualizations from large, diverse data sets in service of continuous improvement of software applications and systems
- Work within an Agile/Scrum environment, contributing to sprint planning, code reviews, and continuous improvement.
- Champion best practices in design, architecture, and AWS cloud-native development.
Identify opportunities to eliminate or automate manual processes and recurring issues to improve the overall operational stability of the platform
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Experience with distributed streaming platform (Kafka)
- Proficient in coding in one or more languages: Core Java, Spring boot
- Demonstrated knowledge within a technical discipline: Big data stack – Spark, S3, Flink, Cloud technology, AWS, Databricks, Core Java, Spring boot, artificial intelligence)
- Strong understanding of data, data modeling and database methodologies and architecture disciplines
- Advanced SQL and data management knowledge
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) 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.
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Experience with AI tools like Claude / Github co pilot
- AWS Cloud Certification and other relevant certifications are a plus
- Data Engineering Experience
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