Director of Software Engineering-HR Domain

JPMorgan Chase & Co.•Jersey City, NJ

17h•$204,250 - $285,000

About The Position

As a Director of Software Engineering at JPMorgan Chase within Corporate Technology – HR, Pay & Time Technology, you provide deep, hands-on technical leadership across multiple application teams while remaining close to the code. You set the engineering bar, architect and build highly scalable solutions, and drive relentless innovation—helping the firm remain at the forefront of industry trends, best practices, and technological advances. In this role you design and build custom, highly scalable applications on AWS that power Compensation, Benefits, Payroll, and Time for the largest bank in the world. You lead engineering for a portfolio of applications that must never go down, blending modern serverless design, multi-region active-active resiliency, and AI-native development to deliver continuously across Web, Mobile, and conversational interfaces.

Requirements

Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.
Deep, current, hands-on expertise developing on AWS with serverless design patterns (e.g., Lambda, API Gateway, DynamoDB, EventBridge, Step Functions)
Expert in designing and operating multi-region active-active applications with high-availability, resiliency, and disaster-recovery patterns for systems that must never go down
Strong programming expertise in Java with the Spring Boot and broader Spring framework (e.g., Spring Cloud, Spring Security), and in Python with modern frameworks (e.g., FastAPI, Flask)
Modern full-stack development across Web, Mobile, and conversational interfaces, including front-end frameworks (e.g., React, TypeScript) and API-first design using GraphQL and REST
Demonstrated experience with AI-native development—agentic workflows, prompt engineering, and loop engineering—using tools such as Claude Code, Copilot, or similar
Experience building MCP servers and custom agents integrated with conversational/chatbot platforms (e.g., Moveworks), engineered for high accuracy and hallucination mitigation
Strong command of CI/CD, test-driven development (TDD), Infrastructure as Code, and Pipeline as Code, with automated testing and security embedded in pipelines
Domain experience building applications across Compensation, Benefits, Payroll, or Time
Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse.

Nice To Haves

Experience with microservices and event-driven architecture using frameworks such as Spring Boot, Spring Cloud, and messaging/streaming platforms (e.g., Kafka)
Experience with containerization and orchestration (e.g., Docker, Kubernetes) and GitOps-based deployment on AWS
Experience integrating large vendor/payroll ecosystems and delivering end-to-end automation toward touchless processing
Experience evaluating and operationalizing emerging GenAI/agentic tooling with strong controls in an enterprise setting
Experience leading globally distributed engineering teams
Proven experience building secure code using guardrails appropriate for a highly regulated industry

Responsibilities

Architects, builds, and operates custom, highly scalable applications on AWS using serverless design patterns, delivering mission-critical Compensation, Benefits, Payroll, and Time capabilities
Designs and runs multi-region active-active applications engineered for continuous availability—resilient, self-healing, and built to never go down—for a large, regulated, globally distributed enterprise
Leads hands-on development across the full stack—Web, Mobile, and conversational chat—building robust services with Java and Spring Boot, Python, and modern front-end frameworks, and setting standards for clean, secure, testable, and maintainable code
Drives AI-native engineering: agentic development workflows, prompt and loop engineering, and AI-assisted development with Claude Code, Copilot, or similar tools to accelerate delivery while maintaining strong controls
Builds MCP (Model Context Protocol) servers and custom agents that drive accurate, low-latency interactions with conversational platforms such as Moveworks—engineered for high accuracy and no hallucinations through grounding, tool/function calling, and guardrails
Establishes and enforces modern engineering practices—CI/CD, test-driven development (TDD), Infrastructure as Code, Pipeline as Code, automated security scanning, and observability
Manages and continuously innovates across a portfolio of applications, balancing rapid, iterative delivery with operational stability, security, and compliance-by-design
Champions secure-by-design development with guardrails appropriate for a highly regulated industry, supporting controls, statutory and tax considerations, segregation of duties, and access management
Partners with product, platform, and operations stakeholders to translate needs into pragmatic, high-quality technical solutions; hires, mentors, and grows strong engineers; and champions the firm's culture of diversity, opportunity, inclusion, and respect
Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, 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 and support capacity unlock initiatives at scale.