Senior Lead Software Engineer - Solution Engineer

JPMorganChase • Jersey City, NJ

1d

About The Position

As a Senior Lead Software Engineer at JPMorganChase within the Consumer and Community Banking technology team, you will contribute to an agile team building and delivering secure, stable, scalable technology products. The role drives business impact through technical expertise and problem-solving across multiple technologies and applications.

You will provide technical guidance, develop and review production code, and lead end-to-end architecture and solutioning for Trust & Security data and integration capabilities. This includes taking solutions from concept and proof of concept through reference architecture and production-ready design, and defining target-state roadmaps and migration paths. You will design Kafka streaming solutions and data contracts, build publishing patterns for analytical platforms, and lead service and pipeline engineering in Java. The role also covers data-store architecture, REST and GraphQL integrations, observability, data governance, and operational readiness.

You will promote approved AI-assisted engineering practices and automation across teams, establishing validation standards for security, correctness, testing, and code quality. You will also help ensure responsible use of AI tools and encourage reuse of proven patterns across the software development lifecycle.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Advanced capability in one or more programming languages or frameworks, including Java, Kafka, Spark, or Flink.
• Proven experience combining data architecture and solution engineering in large-scale production environments.
• Hands-on experience designing and implementing Kafka solutions.
• Hands-on experience publishing data to a lake or data platform using streaming and/or batch approaches.
• Hands-on experience with Cassandra, Oracle, and Java services, pipelines, and streaming or processing components.
• Experience with schema registry and data contract design and governance.
• Experience building APIs and integrations using REST and GraphQL.
• Strong SDLC discipline, including CI/CD, testing strategy, code review, production support, and observability.
• Ability to work independently with little to no oversight, with strong problem-solving and rapid-learning skills.
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools, including setting team expectations for validating AI outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations.
• Experience coaching senior engineers or leads on compliant AI usage patterns and controls.

Nice To Haves

• Familiarity with Trust & Security domains such as fraud, IAM, device trust, cyber signals, third-party risk, and data loss prevention.
• Experience with stream-processing frameworks such as Kafka Streams, Flink, or Spark Streaming, and real-time enrichment or correlation patterns.
• AI/ML knowledge and feature-store patterns, including online/offline consistency and feature publishing and consumption.
• Practical cloud-native experience, particularly in AWS-based ecosystems, and platform modernization efforts.
• A track record of driving reuse-first patterns and setting engineering standards across teams without direct people management.
• Experience with graph databases; TigerGraph is preferred.

Responsibilities

• Provide technical guidance and direction to support the business, technical teams, contractors, and vendors.
• Develop secure, high-quality production code and review and debug code written by others.
• Drive adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Establish measurable validation standards for AI-assisted engineering, including secure coding, peer review, and automated testing.
• Promote reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Own end-to-end architecture and solutioning for Trust & Security data and integration capabilities, from concept and proof of concept through reference architecture and production-ready design.
• Define target-state roadmaps and migration paths.
• Design and implement real-time Kafka streaming solutions, including ordering, idempotency, replay, dead-letter queues, scalability, and operational readiness.
• Define and enforce data contracts and governance, including schema registry strategy, schema evolution and compatibility, ownership, validation, and freshness and quality expectations.
• Build data publishing patterns to the lake or analytical platform for streaming and batch use cases, with observability, data-quality checks, lineage and metadata hooks, and access controls.
• Lead solution engineering for Java services and pipelines.
• Architect and model Cassandra and Oracle data stores for their intended use cases.
• Design REST and GraphQL service interfaces and integrations, including API and error contracts, SLAs/SLOs, and backward-compatible change practices.
• Use software development lifecycle tools, approved AI-assisted development capabilities, and automation to improve value at scale.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed