Software Engineer III

JPMorgan Chase · ✓ Verified company
📍 Mumbai, Maharashtra, India · On-site · Full-time

About the role

  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 Consumer and Community Banking, 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 - Designs, builds, and supports batch processing systems and data pipelines (e.g., scheduled/triggered workflows, ETL/ELT processing, backfills/reprocessing), including operational monitoring, alerting, and incident triage - Implements and enforces data management concepts such as data quality, validation, metadata, lineage, access controls, retention, and auditability aligned to platform standards - Builds and maintains APIs and backend services using Spring Boot, including integration patterns, service contracts, error handling, authentication/authorization integration, and documentation - Leverages AWS cloud services to deliver scalable, resilient, and cost-aware solutions; applies security best practices such as IAM least privilege, encryption, secrets management, and logging - 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 - 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 - Strong coding ability in Java and/or Python, with production experience building reliable services and data processing components - Hands-on experience building and operating batch processing systems and associated data workflows in production environments - Strong knowledge of AWS cloud services and cloud-native engineering practices (security, scalability, resiliency, observability, cost awareness) - Practical experience building APIs using Spring Boot (REST services, validation, testing, performance tuning, documentation) - 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   Preferred qualifications, capabilities, and skills - Familiarity with modern front-end technologies and Exposure to cloud technologies - Experience with data platform patterns (data lake/warehouse, distributed processing frameworks, orchestration) and implementing data quality/metadata/lineage capabilities at scale - Experience with infrastructure-as-code and automated environment provisioning (e.g., Terraform/CloudFormation or equivalent), and strong observability practices (metrics/logging/tracing)