Join our innovative team and shape the future of software development.
As a Director of Software Engineering at JPMorgan Chase within the Commercial & Investment Banking you will deliver a wide range of solutions that enable JPMorgan's Operations team to digitize their daily work slate, as well as provide our external clients with digital platforms to complete their post trade actions with JPMorgan. You will be responsible for highly inspired and inquisitive technologists who are already developing and deploying applications to the highest standards.
This is a hands on role with a clear expectation that you will spend a portion of your time in active software development.
Job Responsibilities:
- Delivers best in class technology solutions on modern tech stack adhering to the firm's processes, controls, and data hygiene standards.
- Collaborates with technology and business partners across levels to enable teams deliver robust solutions at scale and speed.
- Leads migration and transformation initiatives. Engages in the planning, architecture, design, and development of solutions that satisfy business requirements
- Delivers using agile methodology with CI/CD and automated testing and deployment capabilities using devops
- Develops people on technical, domain and leadership capabilities with active coaching. Ability to work proficiently and effectively in an Agile / Scrum feature team environment
- Drives execution capabilities and efficiencies across the organization
- Interacts with senior leadership in India, UK and US to develop strategy for the application platform
- Utilizes excellent organizational skills, proven analytical, planning, problem solving and decision-making skills. Fosters diversity & inclusion
- Creates a customer obsessed centric environment for team and contributors.
- 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.
Required qualifications, capabilities and skills:
- Formal training or certification on large scale technology program 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
- Professional experience working in an agile, dynamic and customer facing environment
- At least 5 years of recent hands-on professional experience (actively coding) working as a full stack engineer
- Extensive experience with using a JVM language
- Understanding of distributed systems and cloud technologies (AWS, GCP, Azure, etc.). Understanding of AOP and dependency injection frameworks (Spring/SpringBoot)
- Strong understanding of design patterns, technical standards, enterprise architecture, microservices architecture, domain modelling and interface definitions, service communication methods, data modelling.
- Strong understanding of transactional semantics, race conditions, memory models, networking, operating systems, databases, data structures and algorithms. Understanding of RESTful APIs and web technologies. Understanding of relational and no-SQL databases (Cassandra, MongoDB)
- Experience in the all stages of software development lifecycle (requirements, design, architecture, development, testing, deployment, release and support). Experience in automating deployment, releases and testing in continuous integration, continuous delivery pipelines
- A solid approach to writing unit level tests using mocking frameworks, as well as automating integration and end-to-end tests
- 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.
Preferred qualifications, capabilities and skills:
- Understanding of security frameworks (Spring Security, SSL, TLS, HTTPS, etc.)
- Understanding of event driven architectures (Kafka)
- Understanding of distributed tracing and monitoring (Splunk, Dynatrace)
- Understanding of containers (Docker, Kubernetes, etc.)
Skills Required
Agile Methodology, Devops, Docker, Design Patterns, Splunk, Cassandra, Kafka, Kubernetes, Springboot, Dynatrace, Gcp, Restful Apis, Azure, Spring, Mongodb, Aws
