Lead Software Engineer
JPMorgan Chase & Co. (company site, opens in a new tab)5+ yrsHyderabadOn-siteDirect career pageEst. 25–45 LPA
Posted 1d ago
Reach people at JPMorgan Chase & Co.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at JPMorgan Chase & Co. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead end-to-end design, development, deployment of scalable, resilient platform solutions with secure infrastructure alignment.
- Drive technical direction, standards, and cross-functional team leadership to build high-quality platform components and automate engineering processes.
- Utilize data analysis for actionable insights, promote adoption of AI-assisted engineering practices, and mentor engineering teams to improve code quality and operational outcomes.
Minimum Requirements
- 5+ years applied experience in system architecture, application development, testing in large-scale enterprise environments.
- Expert proficiency in Python and/or Java; deep expertise in SQL and NoSQL databases, AWS services including EMR, EKS/ECS, EC2, Event Bus, S3.
- Experience with enterprise monitoring tools (Splunk, Elastic Search, Dynatrace, AppDynamics, Grafana, CloudWatch, Datadog) and CI/CD pipelines (Jenkins, Spinnaker).
- Work Experience Required: 5+ years. Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Technical leader with proven ability to set team standards, lead engineering disciplines, and implement secure, scalable architecture in enterprise environments.
- Experienced in driving AI-assisted software development adoption and ensuring responsible, secure AI usage within engineering workflows.
- Strong background in agile methodologies, SDLC, application resiliency, and securing enterprise-grade software delivery.