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**AWS Software Engineer III-ETL/AI** at JPMorgan. Design and deliver secure, scalable products using AWS S3, Redshift, SageMaker, Lambda. Key responsibilities include software solution execution, secure code development, AI tool usage for code quality and speed, and data analysis for continuous improvement. Required: 3+ years in software engineering, hands-on Python/Java experience, proficiency in AWS services, and strong SQL skills. Preferred: Big Data, data orchestration, event-driven architecture, and reinforcement learning expertise. Join the Market Data Lake Core Data Platform team in Newark, DE.

Compensation: Not specified USD
City: Not specified
Country: United States

Full Job Description

Location: Newark, DE, United States

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As an AWS Software Engineer III-ETL/AI at JPMorgan Chase within the Commercial and Investment Banking - Market Data Lake Core Data Platform team, 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 firms 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
Ensure optimal application performance in production, providing ongoing monitoring, troubleshooting, and end-to-end production support to maintain stability and service reliability

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepted and 3+ years applied experience

Hands-on practical experience in system design, application development, testing, and operational stability

Hands-on experience in Python or Java programming languages

Prior experience building and operating data platforms and services using AWS, including services such as S3, Redshift, SageMaker, and Lambda.

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 databases and data access patterns, including platforms such as Redshift and Oracle, and strong SQL/data querying capability.

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

Practical experience using infrastructure-as-code tooling (e.g., Terraform) and working effectively in a large corporate engineering environment

Preferred qualifications, capabilities, and skills

Big Data / distributed computing experience (best to have), including frameworks such as Apache Spark (and/or Hadoop ecosystem) for large-scale data processing

Experience with data orchestration and workflow scheduling tools (best to have), such as Airflow or similar

Exposure to messaging and event-driven architectures (best to have), including technologies such as Kafka and/or MQ (e.g., IBM MQ or similar)

Experience with containerization and orchestration platforms (best to have), including Docker and Kubernetes, and deploying/operating services in containerized environments

Familiarity with Agentic AI frameworks and patterns (e.g., LangChain, AutoGen, CrewAI, or similar) and experience applying them responsibly in production contexts

Experience with reinforcement learning, prompt engineering, or agent-based simulation, especially where it improves agent reliability and business outcomes

Exposure to modern front-end technologies and patterns for integrating AI/data capabilities into user-facing experiences

Leverage AI, data engineering, and cloud to build secure, scalable productsturning complex data into insight with agents and impact

Full Job Description

Location: Newark, DE, United States

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
Ensure optimal application performance in production, providing ongoing monitoring, troubleshooting, and end-to-end production support to maintain stability and service reliability