Vista previa de la oferta
Sr. Lead Software Engineer - Java/Back-End
senior · Technology / Software Development
When you mentor and advise multiple agile technical teams and move financial risk technologies forward, it’s a big challenge with big impact. Join our team and be an integral part of our agile organization to deliver the best risk solutions for the firm. As a Senior Lead Software Engineer at JPMorgan Chase within Consumer & Community Banking, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Lead the architecture, design, and development of Java/Spring‑based framework APIs and shared components that enable rapid, secure service development across multiple LOBs.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Build low‑latency, high‑throughput APIs and event‑driven systems optimized for extreme transaction volumes and near‑zero downtime.
- Profiling, identifying, and optimizing existing code—including code developed by other team members.
Required Qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Experience with strong architecture, design patterns, engineering best practices, analysis, design, security fundamentals, secure coding practices, and code review skills for internet applications.
- Experience with unit, integration, contract testing; experience with test automation frameworks and pipelines (JUnit, Mockito, Spring Test).
- Expertise in underlying third‑party SDKs/components and protocols: AWS SDKs, HTTP connections, IBM MQ, Kafka, Cassandra, Oracle, GraalVM, TLS 1.3.
- Proficiency in service development using REST and SOAP, strong API design fundamentals; JSON/XML messaging and SOA.
- Knowledge of Databases and Data access frameworks like MyBatis, Hibernate, Oracle, Cassandra, CockroachDB.
- Ability to build with cloud‑native microservices at scale: with Kubernetes/Docker/EKS, service discovery, configuration management; AWS services including NLB, ALB, SQS, Redis, S3, Route 53, API/NAT Gateways, Secrets Manager, IAM, VPC; IaC with Terraform and CloudFormation.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
- Familiarity with Messaging and event streaming API's (Kafka), caching (Redis), and familiarity with both SQL and NoSQL datastores.
- Exposure with observability tooling and practices (metrics, tracing, logs) and performance benchmarking at scale.
- Proficiency in Network/Security: Kerberos, TLS 1.3, OAuth2, ADFS, Envoy Proxy, HAProxy, SpiderMesh, OWASP.
Proficiency in Frameworks and libraries: Spring/Spring Boot, SLF4J, Jackson, Hystrix, JMS.
Preferred qualifications, capabilities, and skills
- Experience developing shared libraries/frameworks adopted by multiple product teams.
- Experience in large‑scale enterprise or financial services.