As an Experienced Software Engineer at JPMorganChase within the Global Technology team, you serve as member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. Depending on the team that you join, you could be developing mobile features that give our customers and clients more control over how they bank with us, strategizing on how big data can make our trading systems quicker, creating the next innovation in payments for merchants, or supporting the integration of our private and public cloud platforms.
Job Responsibilities
- Own end-to-end workflow architecture using Camunda (BPMN/DMN), defining orchestration patterns, boundaries, SLAs, and lifecycle management for critical business processes.
- Lead full-stack delivery of workflow-enabled products, spanning React JS UI (user journeys, forms, dashboards) and backend orchestration services (Java/Python), ensuring cohesive UX-to-process execution.
- Lead delivery of core orchestration services in Java (strong Core Java, concurrency, collections, JVM performance), building resilient and maintainable backend services that support workflow execution at scale.
- Translate requirements into executable process models (BPMN) and decision logic (DMN), partnering with product, operations, and control functions to ensure correctness and auditability.
- Design and implement integrations across multiple enterprise systems including Data Marketplace, ServiceNow, and IAM, using API/event-driven patterns and well-defined interface contracts.
- 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
- Own IAM integration for secure workflow execution and UI access, including authN/authZ, service principals, token handling, entitlement checks, least privilege, and secure secrets management.
- Automate end-to-end request/fulfillment workflows (e.g., data access provisioning via Data Marketplace, approvals/ticketing via ServiceNow, automated fulfillment) with full traceability and operational controls. Engineer reliability for long-running workflows: idempotency, retries/backoff, timeouts, correlation IDs, compensation/saga patterns, and deterministic state transitions.
- Drive performance and scalability of Camunda runtime and workers, tuning job execution, worker patterns, concurrency, batching, and database interactions to meet throughput/latency targets. Establish strong observability and operability standards for workflows and full-stack services: structured logging, metrics, distributed tracing, dashboards, alerting, and runbooks for incident response.
- Build and maintain strong CI/CD for React UI, Java/Python services, and workflow artifacts, working with internal EAC pipelines to implement automated testing, security scanning, quality gates, versioning, and safe rollout/rollback; champion AI-enabled Engineering Excellence by applying approved AI-assisted practices (code review support, test generation, defect detection) with rigorous validation for security, reliability, maintainability, and documentation.
- Hands-on, practical experience in system design, application development, testing, and production operational stability for enterprise-grade platforms.
- Proficiency in Java, React JS and/or Python, including strong fundamentals (clean code, OOP, concurrency as applicable) and building backend services/APIs.
- Proven experience with workflow orchestration using Camunda (BPMN/DMN) and Camunda client/engine libraries (e.g., external tasks/workers, decisioning, process versioning).
- Strong understanding of SDLC end-to-end, from requirements and design through build, test, release, and operate. Experience delivering within Agile teams and practices, including iterative planning, backlog refinement, and continuous improvement.
- Strong CI/CD capability: building automated pipelines with quality gates (unit/integration tests, linting, security scanning) and operating within internal EAC pipelines to meet engineering standards.
- Working knowledge of application resiliency patterns for long-running processes: idempotency, retries/backoff, timeouts, compensation/saga patterns, and failure recovery.
- Strong focus on security-by-design: secure coding, secrets management, least privilege, and adherence to firm/organizational security expectations. Experience integrating workflows/services with multiple enterprise systems such as Data Marketplace, ServiceNow, and IAM (API/event-driven integration, contract testing, and operational support).
- Demonstrated leadership in AI-enabled engineering using approved AI-assisted development tools (coding, code review, test acceleration, troubleshooting), with clear expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI usage in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and ability to coach engineers on safe, compliant adoption aligned to resiliency and security standards.
- Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Deep expertise with Camunda 7/8 libraries and integrations; hands-on with process versioning/migration strategies, multi-environment operations, and runtime performance tuning.
- Strong experience designing distributed systems / microservices and event-driven orchestration (e.g., Kafka), including replay safety, deduplication, and eventual consistency patterns.
- Advanced Java backend engineering (JVM profiling/tuning, concurrency, performance optimization) and/or production-grade Python services.
- Full-stack engineering capability: strong React JS (TypeScript preferred) for workflow-driven UIs (intake forms, task lists, approvals, dashboards), plus API integration and state management aligned to backend workflows.
- Proven delivery of enterprise integrations across platforms such as Data Marketplace, ServiceNow, IAM, and other internal/external systems using robust API/contract patterns.
- Strong cloud operational experience (deployments, config/secrets, GitOps), including production readiness and environment promotion practices.
- Excellence in observability and reliability (tracing, metrics, alerting, incident management, post-incident improvements) for long-running workflows. Demonstrated leadership in AI-enabled Engineering Excellence, using approved AI tools with disciplined validation and responsible AI practices (data sensitivity, security, compliance).