Lead Software Engineer - Python Unix

JPMorgan Chase & Co.; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

JPMorgan Chase in Bengaluru seeks a Lead Software Engineer to drive resilience for critical applications in Markets. You will lead a team, shape SRE practices, and mentor engineers while solving complex reliability challenges.

You will conduct resiliency design reviews, guide incident responses, and enable AI-assisted workflows across the SDLC to improve service levels and security.

Qualifications

• Formal training or certification in software engineering with 10+ years of experience.
• Demonstrated proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and other site reliability best practices.
• Programming language - Python.
• Experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows with strong validation habits and awareness of data sensitivity.
• Ability to evaluate AI-assisted operational recommendations for correctness and risk, define guardrails for team usage, and ensure outcomes align to resiliency and security expectations.
• Proficient knowledge and experience in observability such as white and black box monitoring, SLO alerting, and telemetry collection.
• Proficient with CI/CD practices and tooling.
• Proficient with container and container orchestration.
• Experience with troubleshooting common networking technologies and issues.
• Advanced knowledge of software applications and technical processes with emerging depth in one or more technical disciplines, and actively self-educates to evaluate and recommend suitable new technologies

Responsibilities

• Champion site reliability culture; share knowledge via internal forums and communities of practice.
• Leads initiatives to improve reliability and stability using data-driven analytics to improve service levels, identifying bottlenecks.
• Drives collaboration to establish service level indicators and objectives with stakeholders.
• Uses enterprise-authorized AI capabilities to accelerate major-incident triage, troubleshooting, and post-incident analysis.
• Serves as main contact during major incidents to resolve issues quickly and avoid financial loss.
• Offers a high level of technical expertise and mentorship to engineers.
• Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices with traceability, resiliency, and security controls.

Skills

Python

Reliability engineering

Observability

CI/CD

Container orchestration

Networking troubleshooting

AI in SRE

Mentoring

Education

Formal training or certification in Software Engineering

Job description

Job Description:

Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank, Markets you hold a leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them. Take lead and conduct resiliency design reviews, break up complex problems into digestible work for other engineers, act as a technical lead for medium to large-sized products, and provide advice and mentoring to other engineers.

Job responsibilities

• Consistently models and champions site reliability culture and practices, documents and shares knowledge within your organization via internal forums and communities of practice


• Leads initiatives to improve the reliability and stability of your team’s applications and platforms using data-driven analytics to improve service levels, proactively identifying and solving technology-related bottlenecks in areas of expertise


• Drives collaboration with your team to identify comprehensive service level indicators and the stakeholder partners to establish reasonable service level objectives and error budgets with your customers


• Uses enterprise-authorized AI capabilities within the work environment to accelerate major-incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.


• Serves as the main point of contact during major incidents for your application and has the skills to identify and solve the issue quickly to avoid financial loss to the business


• Offers a high level of technical expertise within one or more technical domains and provides advice and mentorship to other engineers


• Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls.

Required qualifications, capabilities, and skills

• Formal training or certification on Software Engineeringconcepts and 10+ years applied experience


• Demonstrated proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and other site reliability best practices


• Programming language - Python.


• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g., incident investigation support and knowledge capture) with strong validation habits and awareness of data sensitivity.


• Ability to evaluate AI-assisted operational recommendations for correctness and risk, define appropriate guardrails for team usage, and ensure outcomes align to resiliency and security expectations.


• Proficient knowledge and experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection


• Proficient with continuous integration and continuous delivery practices and tooling


• Proficient with container and container orchestration


• Experience with troubleshooting common networking technologies and issues


• Advanced knowledge of software applications and technical processes with emerging depth in one or more technical disciplines, and actively self-educates to evaluate and recommend suitable new technologies

Requirements: