Push the limits ofwhatspossible with us as an experienced member of our Software Engineering team.

As a Lead Software Engineer at JPMorgan Chase within the Enterprise Technology Data Protection & Recovery product line, you will be an essential member of an agile team dedicated to enhancing, building, and delivering trusted,market leadingtechnology products in a secure, stable, and scalable manner. Your role will involve promoting significant business impact through your skills and contributions,utilizingyour deep technicalexpertiseandproblem solvingmethodologies to address a wide range of challenges across technologies and applications. You will collaborate with global product and engineering teams and platform stakeholders to deliver resilient, efficient, and innovative solutions that advance the firm27s strategicobjectives.

Job Responsibilities

• Providehands ontechnical leadership and guidance across teams; serve asfunction widesubject matter expert in resiliency and recovery observability.
• Ownend to endarchitecture for critical Java services: define domain boundaries, API contracts, event schemas, andcross-servicestandards; steward architectural decision records.
• Design, develop, and review secure,high qualityproduction code in Java; debug complex issues; mentor engineers through code reviews and technical coaching.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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.
• Drive resilient service design: drive and manageavailabilitySLOs, latency budgets, and error budgets.
• Partner with the engineeringleadthe secure SDLC: conduct threat modeling; integrate SAST/DAST and dependency risk management; ensure encryption in transit/at rest and robust secrets hygiene; overseeauthN/authZpatterns.
• Champion observability and SRE practices: instrument metrics/logs/traces; design actionable alerts; author runbooks; lead incident response, blameless postmortems, and continuous reliability improvements.
• Advance data protection and recovery capabilities:maintainevidence chain of custody and immutable operation, restore validation exercises and auditability.
• Enhance existing systems by analyzingobjectives, preparing action plans, andidentifyingopportunities for performance, reliability, and operability improvements.
• Help support CI/CD quality within the product line, partnering with the engineering and product teams: codify automated tests (unit, integration, contract, performance), coverage targets, pipeline quality gates, and progressive delivery (canary/blue-green) with rollback plans.
• Contribute to the engineering community as an advocate of firmwide frameworks, tools, and best practices; add to team culture by fostering diversity, inclusion, and respect.
• Support critical environments (Development, QA, Simulation, Production) and leadon-callobligations for owned services, ensuring operational stability andtimelyresolution of incidents.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• 8+ of experience years with expert level Javaproficiency, including collections, concurrency, memory management, and performance tuning; experience with profiling tools. Able to walk through applied examples designing andoperatingdistributed Java systems.
• Strong experience with Spring Boot andmicroservices; APIfocusedevent drivendesign and idempotency; schema evolution and compatibility.
• Expert-level experiencing designing and implementing Python-based microservices.
• Deep knowledge of resiliency engineering patterns and disaster recoveryobjectives(RTO/RPO) withhands onpractice running DR tests and chaos/resilience exercises.
• Secure SDLCexpertise: threat modeling, SAST/DAST integration, dependency risk/SBOM management, secrets handling, encryption standards, and robust authentication/authorization.
• Streaming and messaging: practical experience with Kafka (topic design, partitioning, consumer group scaling, transactional/exactly-oncesemantics) and other messaging platforms asrequired.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) 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, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Observability: instrumentation of metrics/logs/traces, alerting design, runbooks, incident management, and postmortems.
• DevOps/SDLC:proficiencywith build tools, CI/CD systems, and version control (Git) with automated pipeline governance.
• Cloud-hybriddelivery: containers and orchestration, infrastructure as code,multi-AZ/region architectures, andcost efficientscalability;hands onexperience with AWS and awareness of other cloud providers.
• Ability to independently tackle complex design and functionality problems with minimal oversight; excellent technical communication and mentoring skills.

Preferred qualifications, capabilities, and skills

• Experience with service mesh, API gateways, and contract governance at scale.
• Familiarity with modernfrontendtechnologies for internal tooling or dashboards.
• Proficiencyin one or moreadditionalprogramming languages (e.g., Python) for API delivery and management, tooling, automation, or data tasks as well as partnering with other delivery teams.
• Experienceestablishingengineering standards across multiple teams and leading technical working groups.
• Knowledge of UNIX/Linux and shell scripting for operational tooling and automation.

Leadership and collaboration expectations

• Act as a trusted technical leader across regions, influencing peers and decisionmakers to adoptleading edgetechnologies and best practices in resilience and security.
• Mentor engineers at multiple levels, elevate code quality and design rigor, and contribute to internal forums and tech talks todisseminatebest practices.
• Build strong working relationships with platform partners across Product Development, Operations, Risk/Controls, and other firmwide functions to deliver competitive, scalable solutions.