
Software Engineer III-SRE
JPMC · Bengaluru, Karnataka, India
Strong hiring record · median 28 days open
Hiring signal
Actively hiring
Posted yesterday · still listed on the employer's own board · How we score
All reasons
In its favour
- Posted yesterday
- Still listed on the employer's own board
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 Commercial & Investment Bank, 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
- Deliver end-to-end software solutions (design, development, troubleshooting) with strong problem decomposition and innovative thinking beyond routine approaches.
- Build and maintain secure, high-quality production code, including synchronous integrations and algorithm maintenance.
- Produce architecture/design artifacts for complex applications and ensure implementation adheres to design constraints.
- Analyze large, diverse datasets to create insights, visualizations, and reporting that drive continuous improvement.
- Proactively identify hidden issues/patterns and use them to improve coding hygiene, reliability, and system architecture.
- Champion site reliability culture: define, educate, and operationalize SLOs/SLIs/error budgets with product, engineering, and stakeholders; monitor and review regularly.
- Drive delivery excellence through self-learning, issue/blocker resolution, and robust change & release management practices.
- 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.
- Lead cross-team operational responsibilities including hosting platform/infrastructure planning, data center migrations, partner engagements, audits/application hygiene, and contribute to engineering communities, knowledge sharing, and inclusive, resilient team culture.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Hands-on experience across system design, application development, testing, and production/operational stability.
- Strong coding skills in one or more modern programming languages.
- Proven ability to develop, debug, and maintain enterprise-scale code, including database querying. Solid understanding of the Software Development Life Cycle (SDLC) and end-to-end delivery.
- Practical experience with Agile ways of working, including CI/CD, application resiliency, and security practices. Exposure to modern technical domains such as cloud, AI/ML, and/or mobile, and their supporting technical processes.
- Excellent communication and stakeholder management, adapting messages for senior business and junior technologists.
- Pragmatic mindset to drive technical re-engineering/modernization while continuing business delivery.
- Deep expertise in SRE best practices: reliability, scalability, performance, security, enterprise architecture, and toil reduction; able to promote SRE culture within the team.
- 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.
- Strong operational tooling knowledge: file transfers, SSL/certificates, load balancers, job scheduling, monitoring, backup/capacity, plus containers/orchestration (Docker/ECS/Kubernetes), CI/CD tools (Jenkins/GitLab/Terraform), and network troubleshooting; experience with enterprise-authorized AI-assisted dev tools and responsible AI use (validation, security, data sensitivity).
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