✨ AI Summary
As a Software Engineer III at JPMorganChase within Corporate Technology, you will be a seasoned member of an agile team responsible for designing and delivering market-leading technology products securely and scalably. Your duties include executing software solutions, design, development, and technical troubleshooting, creating secure and high-quality production code, and leveraging enterprise-authorized AI coding assist tools to improve code quality and productivity. You will produce architecture and design artifacts, gather and analyze data for continuous improvement, and proactively identify problems and patterns in data to drive system enhancements.
Required qualifications include formal training or certification in software engineering with 3+ years of applied experience, hands-on experience in system design, application development, testing, and operational stability. You should be proficient in developing, debugging, and maintaining code in a corporate environment using modern programming languages and database querying languages, and experienced with enterprise-authorized AI-assisted software development tools. A solid understanding of the Software Development Life Cycle, agile methodologies, Machine Learning, Python, PySpark, Big Data, data pipelines, strong SQL skills, Spark cluster optimization, and AWS services (EMR, EC2, S3, CloudWatch) and Databricks for data pipelines and model deployment are also necessary.
🎁 Benefits & Perks
Comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching.
Requirements
Requires formal training or certification on software engineering concepts and 3+ years of applied experience. Must have hands-on practical experience in system design, application development, testing, and operational stability. Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages is essential. Familiarity with enterprise-authorized AI-assisted software development tools, responsible AI use, the Software Development Life Cycle, and agile methodologies is required. Proficiency in Python, PySpark, Big Data, Data pipelines, Machine Learning, strong SQL skills, experience configuring Spark clusters, and hands-on experience with AWS services (EMR, EC2, S3, CloudWatch) and Databricks are necessary.
Description
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within the Corporate Technology, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- 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.
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- 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.
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Good knowledge of Machine Learning modelling as an engineer
- Experience in working with one or more programming language(s) and framework(s) (i.e., Python, PySpark, Big Data, Data pipeline, Machine Learning, etc.)
- Strong SQL skills with ability to validate features and data quality at scale
- Experience configuring and optimizing Spark clusters for processing large data.
- Hands-on experience working with AWS services including EMR, EC2, S3, and CloudWatch
- Working knowledge on Databricks in creating Data Pipelines, Machine learning models deployment.
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Experience in Cloud Technologies (i.e., AWS - Databricks preferred)
- Understands Python Machine Learning libraries and ecosystems (i.e., Pandas, Numpy, etc.)
- AWS certifications (e.g. Solutions Architect Associate)
- Exposure to workflow orchestration tools (Apache Airflow, Control M etc)