Principal Software Engineer - Kinexys

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 190,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. in Jersey City seeks a Principal Software Engineer to lead architecture for public-chain integrations and on-chain/off-chain workflows, driving secure, scalable blockchain solutions that connect enterprise systems with public networks.

You will mentor senior engineers, set engineering standards, and advocate security-by-design and AI-enabled development practices across squads, while collaborating with executives on strategic technology decisions.

Qualifications

• 7+ years of applied software engineering experience.
• Experience building distributed systems or blockchain infrastructure.
• Strong system design, performance and resilience skills.
• Leadership track of shipping complex platforms at scale.

Responsibilities

• Own end-to-end architecture for public-chain connectivity and on-chain/off-chain workflows.
• Lead design reviews, set engineering standards, and mentor senior engineers.
• Drive security-by-design practices including key management and threat modeling.
• Evaluate protocols/partners and contribute to open standards.
• Architect and govern AI-enabled engineering workflows with guardrails.

Skills

Distributed systems

Blockchain infrastructure

System design

Leadership

Agentic AI

Security by design

Stakeholder communication

RPC reliability

Education

Software engineering certification

Tools

AI-assisted development tools

SDLC tools

Job description

We're seeking a Principal Software Engineer to lead technical strategy and hands-on delivery of Kinexys integrations and products across the public blockchain ecosystem. Promote secure, scalable blockchain solutions that connect enterprise systems with public networks and digital asset platforms.

Job Responsibilities

• As a Principal Software Engineer at JPMorgan Chase within Payments & Global Banking Technology, you will own end-to-end architecture for public-chain connectivity, interoperability, and on-chain/off-chain workflows.
• Lead design reviews, set engineering standards, and mentor senior engineers across multiple squads.
• Drive security-by-design (key management, smart contract assurance, threat modeling, monitoring/incident response).
• Evaluate protocols/partners, contribute to open standards where relevant, and shape the public-chain roadmap.
• Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
• 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.

• Influences leaders and senior stakeholders across business, and advises cross-functional teams on technological matters within domain of expertise

  Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 7+ years appliedexperience
• Deep experience building distributed systems and/or blockchain infrastructure (public chain integrations, node/provider architecture, indexing, RPC reliability, L2/bridging patterns).
• Strong system design, performance, and resilience engineering; ability to operate in regulated environments.
• Proven technical leadership with a track record of shipping complex platforms at scale.
• Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
• Ability to present and effectively communicate with Senior Leaders and Executives