As a Senior Principal Software Engineer at JPMorganChase within the Chief Technology Office (CTO), you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. 

As the Senior Principal Software Engineer you will work on a rare greenfield opportunity to solve for one of the fastest-growing threats in enterprise technology - Software Dependency Risk. As AI-assisted development accelerates the adoption of open-source and commercial packages across the firm, understanding what software your applications depend on — and whether it's healthy, secure, and compliant — has never been more critical. JPMorgan Chase's answer to that challenge: a firm-wide platform that gives 60,000 developers and their engineering leaders visibility into the dependency health of 6,000+ applications. We are past ideation and into the market — an early product in hand, the roadmap ahead, and a mandate to build something that becomes foundational infrastructure for how the firm manages software risk at scale.

Job responsibilities

• Define and own the platform architecture across data ingestion pipelines, dependency graph modeling, and developer-facing APIs on AWS and Java.

• Serve as the technical authority — the person the team reaches for on design decisions, performance problems, and build-vs-buy calls

• Partner with the ED of Engineering on technical strategy and roadmap sequencing

• Mentor senior engineers and raise the technical bar across the team

• Advises and leads on the strategy and development of multiple products, applications, and technologies across a portfolio

• Creates novel code solutions and drives the development of new production code capabilities across teams and functions

• Lead delivery of the core platform build-out: data ingestion pipelines, dependency graph modeling, developer-facing surfaces, and firm-wide integration. 

• Sets strategy and operating standards for agentic AI-enabled engineering across a portfolio (using enterprise-authorized tools within the work environment) to drive measurable improvements in delivery speed, reliability, and code quality (e.g., AI-orchestrated SDLC/TLM automation, release readiness gating, incident triage/root-cause acceleration, and large-scale refactoring/test modernization), while defining guardrails for validation, security, resiliency, and reuse across teams and functions.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

• Build an agentic-first development practice — where AI tools (including Claude) are embedded into how the team designs, codes, reviews, and ships.  Set the standard for what a high-performing, AI-augmented engineering team looks like inside a regulated, large-scale enterprise

• Operate as a senior engineering voice, building relationships and credibility across teams beyond your direct organization.  Represent engineering in cross-functional discussions with security, risk, compliance, and firm-wide platform partners.  Engage with senior stakeholders with clarity and conviction — translating deep technical work into business impact

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering concepts and 10+ years of applied experience. 

• Experience operating at both high altitude (architecture, strategy) and ground level (code reviews, pairing, debugging production issues)

• Expert in one or more programming language(s) – Java & Python.

• Experience designing and scaling data-intensive platforms — data structures, data pipelines, large-scale ingestion, graph or dependency.

• Practical experience successfully delivering from concept, design, application development, testing, first release, operational stability and to iterative improvement.

• Practical experience with AI-first development practices — using LLMs and agentic tools to accelerate software delivery.

• Practical experience successfully delivering from concept, design, application development, testing, first release, operational stability and to iterative improvement.

• Demonstrated experience designing and scaling agentic AI-enabled development patterns (using enterprise-authorized tools within the work environment) across teams/functions, including establishing governance for human-in-the-loop validation, traceability/auditability, and secure handling of sensitive inputs/outputs.

• Strong understanding of responsible AI use and control expectations at scale, including security/resiliency implications, data sensitivity, and risk-based governance; ability to advise senior leaders on safe adoption, reuse, and measurable outcomes.

• Experience applying expertise and new methods to determine solutions for complex technology problems across various technical disciplines

• Extensive practical cloud native experience (AWS)

Preferred qualifications, capabilities, and skills

• Experience with Greenfield architecture. 

• Experience delivering AI/ML solutions in financial services, capital markets, or operations-focused environments

• Experience working in highly regulated environments with strong model risk, governance, or control expectations

• Experience designing scalable system architectures for AI products and platforms across multiple stakeholder groups