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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 - Research & Development for the NEO and BRIE Platforms at JPMorgan Chase within the Commercial and Investment Banking - Data Analytics Payment Team, you lead multiple engineers and set the technical direction for how emerging technologies are evaluated, proven, and adopted across our agent runtime and data platform estate. You manage the team's output, practices, and collaboration, and you are responsible for anticipating the needs of the platforms and the stakeholders they serve in a secure, stable, and scalable way. Job responsibilities

• Provides overall direction, oversight, coaching, and career development for a team of 4-5 software engineers across varying experience levels, cultivating a high-performing R D function
• Owns the research and development agenda for the NEO agent runtime and BRIE data platforms, translating platform strategy into a prioritized book of work spanning query federation, policy, storage, cataloging, and caching/memory
• Leads structured technology evaluations and proofs of concept - defining success criteria, benchmarking candidates, and producing clear recommendations that hold up to architectural and security review
• Drives team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and consistent validation standards (secure coding, peer review, automated testing), while promoting reuse of effective patterns across 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.
• Reviews and debugs code and designs authored by the team, and remains hands-on enough to guide critical technical decisions
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability within existing systems and information architecture
• Makes decisions that influence team resources, budget, and tactical operations, and is accountable for those outcomes
• Ensures successful collaboration across engineering teams, product, and platform stakeholders, and communicates findings and trade-offs to senior leadership .

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