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Senior Manager of Software Engineering - Research & Development for the NEO and BRIE Platforms at JPMorgan Chase, Jersey City, NJ

Senior Manager of Software Engineering - Research & Development for the NEO and BRIE Platforms at JPMorgan Chase in Jersey City, NJ. Est. up to $250k. Apply with swipeandhired.

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

Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience, with 2+ years leading and coaching teams of technologists

Hands-on practical experience delivering system design, application development, testing, and operational stability

Experience hiring, developing, and recognizing talent, and setting expectations for team output and engineering practices

Advanced in one or more programming language(s): Java, Python, or Rust

Demonstrated experience leading effective use of approved AI-assisted software development tools, with the ability to set team expectations for validating AI outputs for correctness, performance, and security

Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling of inputs/outputs

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.

Proficient in all aspects of the Software Development Life Cycle

Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, distributed data systems)

In-depth knowledge of the financial services industry and their IT systems

Preferred qualifications, capabilities, and skills

Experience evaluating and operating query federation engines (e.g., Starburst/Trino) across heterogeneous data sources

Experience with centralized policy and authorization engines (e.g., OPA/Rego, OpenFGA) for runtime and structural access control

Experience deploying and tuning columnar/OLAP stores (e.g., ClickHouse) in both on-premises and AWS environments

Familiarity with open-source data catalog solutions and open table formats (Apache Iceberg) for lakehouse architectures

Experience with caching and in-memory data solutions (e.g., Redis) for low-latency retrieval and agent/session memory

Exposure to LLMs, RAG architectures, vector databases, and embedding-based retrieval systems

Proficiency with Infrastructure as Code (Terraform) and containerized deployments (Docker, Kubernetes)