Manager of Software Engineering - AWS SRE

JP Morgan Chase; Hyderabad; On-site; INR 3,200,000 - 5,200,000; Full time

Job summary

JPMorgan Chase in India seeks a hands-on Manager of Software Engineering to lead multiple engineering teams, drive delivery priorities, and ensure secure, scalable technology solutions for Consumer and Community Banking Technology.

You will guide teams through SDLC, implement AI-assisted engineering practices, and manage risk, compliance, and stakeholder expectations while coaching engineers for career growth.

Qualifications

• 5+ years of applied software engineering leadership experience.
• Proven coaching, mentoring, and developing engineers or technical contributors.
• Experience leading technology projects from planning through delivery and production support.
• Experience managing technologists across delivery priorities, performance expectations, risk management, and stakeholder commitments.
• Leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams.
• Ability to define ways of working for AI-assisted engineering, including review expectations, validation routines, outcome measurement, and secure data handling.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, resiliency, security, and governance expectations.
• Proficiency across the Software Development Life Cycle, including requirements analysis, design, development, testing, deployment, and support.
• Advanced understanding of agile delivery practices, CI/CD, application resiliency, security, and production readiness.
• In-depth knowledge of financial services technology environments, IT systems, control expectations, and practical cloud-native engineering.

Responsibilities

• Guide immediate teams of software engineers on daily tasks, technical decisions, delivery priorities, and quality expectations.
• Set clear standards for team output, engineering practices, collaboration routines, and accountability across multiple workstreams.
• Lead adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes.
• Establish expectations for human validation, secure handling of inputs and outputs, and consistent use of reusable engineering patterns.
• Apply knowledge of the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to increase automation value.
• Anticipate dependencies across teams, platforms, and delivery partners to support timely execution of products and applications.
• Manage stakeholder relationships by communicating delivery status, risks, trade-offs, and escalation needs with clarity and accountability.
• Ensure team delivery aligns with compliance standards, SLAs, business requirements, and applicable control expectations.
• Coach engineers and technical leads on delivery discipline, responsible technology practices, engineering excellence, and career development.
• Resolve execution issues by identifying root causes, coordinating cross-team action, and strengthening delivery routines to prevent recurrence.
• Improve team effectiveness by using metrics, retrospectives, automation opportunities, and operating feedback to strengthen quality, resiliency, and capacity.

Skills

Experience leadership

Coaching & mentoring

Project leadership

Delivery risk management

AI-assisted development

AI governance & data handling

Responsible AI practices

SDLC & agile

CI/CD & production readiness

Financial services tech domain

Tools

SDLC toolchain

Job description

This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

As a Manager of Software Engineering at JPMorgan Chase within Consumer and Community Banking Technology, you lead multiple engineering teams and manage day-to-day implementation activities that deliver secure, reliable, and scalable technology solutions. You identify and escal risks, remove delivery impediments, and help ensure your teams' work aligns with compliance standards, business requirements, service level agreements, and tactical best practices. You also guide responsible adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, resiliency, and operational outcomes while maintaining appropriate human oversight and secure handling of data.

Job Responsibilities

• Guide immediate teams of software engineers on daily tasks, technical decisions, delivery priorities, and quality expectations.
• Set clear standards for team output, engineering practices, collaboration routines, and accountability across multiple workstreams.
• Lead adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes.
• Establish expectations for human validation, secure handling of inputs and outputs, and consistent use of reusable engineering patterns.
• Apply knowledge of the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to increase automation value.
• Anticipate dependencies across teams, platforms, and delivery partners to support timely execution of products and applications.
• Manage stakeholder relationships by communicating delivery status, risks, trade-offs, and escalation needs with clarity and accountability.
• Ensure team delivery aligns with compliance standards, service level agreements, business requirements, and applicable control expectations.
• Coach engineers and technical leads on delivery discipline, responsible technology practices, engineering excellence, and career development.
• Resolve execution issues by identifying root causes, coordinating cross-team action, and strengthening delivery routines to prevent recurrence.
• Improve team effectiveness by using metrics, retrospectives, automation opportunities, and operating feedback to strengthen quality, resiliency, and capacity.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Demonstrated experience coaching, mentoring, and developing software engineers or technical contributors.
• Experience leading technology projects from planning through execution, delivery, and production support.
• Experience managing technologists across delivery priorities, performance expectations, risk management, and stakeholder commitments.
• Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams.
• Ability to define ways of working for AI-assisted engineering, including review expectations, validation routines, outcome measurement, and secure data handling.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, resiliency, security, and governance expectations.
• Proficiency across the Software Development Life Cycle, including requirements analysis, design, development, testing, deployment, and support.
• Advanced understanding of agile delivery practices, CI/CD, application resiliency, security, and production readiness.
• In-depth knowledge of financial services technology environments, IT systems, control expectations, and practical cloud-native engineering.