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JPMorgan Chase & Co.

Sr Manager of Software Engineering

JPMorgan Chase & Co. · Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

7 h ago Closes in 6d
Principal (10+ yrs) Full-time India
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About the role

The Senior Manager of Software Engineering provides technical direction, coaching, and oversight for multiple engineering teams within the financial technology sector. They are responsible for scaling operating practices, managing budgets, and ensuring the successful delivery of complex technical projects through cross-functional collaboration.

What they look for

Software Engineering Team Leadership Technical Coaching Distributed Systems Cloud-native Architecture AWS Azure CI/CD SDLC AI-assisted Development SRE Mindset Incident Response Stakeholder Management Risk Management Financial Technology Performance Management

Requirements

Candidates must have 10+ years of technology experience with a strong background in core engineering disciplines and leadership. The role requires deep expertise in distributed systems, cloud-native platforms, and the ability to influence stakeholders in a regulated environment.

Full description

When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this.

As a Senior Manager of Software Engineering at JPMorgan Chase within the Consumer & Community Banking, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm.

Job responsibilities

  • Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks
  • Be accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
  • Ensures successful collaboration across teams and stakeholders
  • Identifies and mitigates issues to execute a book of work while escalating issues as necessary
  • Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team
  • Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
  • Creates a culture of diversity, opportunity, inclusion, and respect for team members and prioritizes diverse representation

Required qualifications, capabilities, and skills

  • 10+ years’ technology experience with a degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or related field; strong grounding across core engineering disciplines.
  • Engineering leadership & talent development: led teams of technologists (senior engineers and/or engineering managers); hiring, coaching, performance management, recognition, succession planning; building inclusive, high-performing teams.
  • Strategy-to-execution delivery: translate business outcomes into technical strategy/roadmaps; deliver multi-team, cross-functional programs with strong dependency and RAID management and stakeholder alignment.
  • Distributed systems & architecture depth: strong system design across APIs, microservices and/or event-driven architectures, data stores, and resiliency patterns; sound scalability/latency/fault-tolerance/consistency tradeoffs.
  • Cloud-native & platform engineering: practical experience building on AWS and/or Azure, including containerization and platform capabilities that enable reusable patterns.
  • Developer productivity & SDLC rigor: experience with CI/CD, automation, test strategy, release safety, and quality/velocity improvements across teams.
  • Operational excellence (SRE mindset): observability (metrics/logs/traces), incident response and RCA, SLO/SLA management, and continuous improvement of reliability/run-the-business outcomes.
  • Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
  • Security, risk & executive influence in regulated environments: secure SDLC, IAM/data protection concepts, audit/compliance partnership, change governance, evidence-quality documentation; strong executive communication and ability to influence without authority across Product, Operations, Security, and Compliance; exposure to data-intensive and/or AI/ML-enabled systems where relevant.