Sr Manager of Software Engineering

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.