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 JPMorgan Chase within the AWM LOB, you serve as a seasoned member of an agile team to design and deliver large-scale trusted market-leading technology products in a secure, stable, and scalable way on AWS Cloud. You are responsible for designing, developing and deploying critical AWS based technology solutions across multiple technical areas in support of the firm’s business objectives.
- Distributed data processing (Spark), schema governance, and data quality controls
- Design and develop Messaging patterns with SQS/SNS, DLQs, idempotency, and exactly-once/effective-once processing
- 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.
- RDS/PostgreSQL performance tuning, partitioning, and high availability
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- 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
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Formal training or certification on software engineering concepts and 3+ years applied experience
- 5+ years hands-on practical experience in system design, application development, testing, and operational stability for l arge-scale, event-driven AWS architectures using AWS Lambda, Kubernetes/EKS and ECS workload orchestration, scaling, and resiliency
- 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.
- Design and develop Serverless systems (Lambda), cold start mitigation, and observability
- Designing , implementing and operating large-scale, event-driven AWS architectures
- AWS Lambda, Kubernetes/EKS and ECS workload orchestration, scaling, and resiliency
- Proficient in Serverless systems like AWS Lambda using Messaging Patterns like SQS/SNS and DLQs
- 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 of RDS/PostgreSQL performance tuning, partitioning, and high availability
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Deep Experience in cloud technologies, and Artificial Intelligence Models
- OpenSearch operations, indexing strategy, and cost/performance optimization
- End-to-end observability (metrics, logs, traces), on-call readiness, and incident response
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security