JP Morgan Chase

Runs a consumer bank and an investment bank

Senior Lead Software Engineer - Solution Engineer

Backend EngineeringConfirmed live in the last 24 hours

Full-time$175.8k - $260kIn-person

About the Job

Requirements

Formal training or certification in software engineering concepts and at least five years of applied experience.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Advanced proficiency in one or more of Java, Kafka, Spark, or Flink.
Proven experience combining data architecture and solution engineering in large-scale production environments.
Hands-on experience with Kafka design and implementation; publishing data to a lake or data platform using streaming and/or batch methods; Cassandra and Oracle; and Java services, pipelines, and streaming or processing components.
Experience with schema registry, data contract design, and governance.
Experience building APIs and integrations using REST and GraphQL.
Strong software development life cycle discipline, including continuous integration/continuous delivery, testing strategy, code review, production support mindset, and observability.
Ability to work independently with little-to-no oversight, along with problem-solving and rapid learning ability.
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools at work, such as coding, code review, test acceleration, and troubleshooting, and setting team expectations for validating AI outputs for correctness, performance, and security.
Strong 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 and leads on compliant usage patterns and controls.

Responsibilities

Provide technical guidance and direction to support the business and its 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 across teams to improve code quality, delivery speed, and operational outcomes, including AI-assisted code review and refactoring, test acceleration, release readiness, and incident and root-cause analysis; establish measurable validation standards for secure coding, peer review, and automated testing; promote reuse of proven patterns and automation within the software development life cycle and technology lifecycle management toolchain.
Own end-to-end architecture and solutioning for Trust and Security data and integration capabilities, from concept and proof of concept through reference architecture and production-ready design, including target-state roadmaps and migration paths.
Design and implement real-time streaming solutions using Kafka, including ordering, idempotency, replay, dead-letter queues, scalability, and operational readiness; define and enforce data contracts and governance patterns, 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, producing secure, high-quality production code, and review and debug code written by others.
Architect and model data stores for fit-for-purpose needs across Cassandra, including partitioning, performance and consistency tradeoffs, and resiliency patterns, and Oracle, including schema design, SQL performance fundamentals, and integration patterns.
Design service interfaces and integrations using REST and GraphQL, including API and error contracts, service-level agreements and objectives, and backward-compatible change practices.
Apply knowledge of software development life cycle toolchain capabilities, including approved AI-assisted development and automation, to improve the value realized from automation at scale.

Desired Qualifications

Domain familiarity in Trust and Security areas such as fraud, identity and access management, 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 and correlation patterns; AI and machine learning concepts and feature store patterns, such as online/offline consistency and feature publishing and consumption, are nice to have.
Practical cloud-native experience, particularly in AWS-based ecosystems, and platform modernization efforts.
Track record of driving reuse-first patterns and setting engineering standards across teams without direct people management.
Experience with graph databases; TigerGraph is preferred.

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the Consumer and Community Banking's technology team, 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 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.
Own end-to-end architecture and solutioning for Trust & Security data and integration capabilities (from concept → POC → reference architecture → production-ready design), including target-state roadmaps and migration paths.
Design and implement real-time streaming solutions using Kafka, including reliability patterns (ordering, idempotency, replay, DLQs), scalability, and operational readiness; define and enforce data contracts and governance patterns, including schema registry strategy, schema evolution/compatibility, ownership, validation, and freshness/quality expectations.
Build data publishing patterns to the lake / analytical platform, supporting both streaming and batch use cases with strong observability, data quality checks, lineage/metadata hooks, and access controls.
Lead solution engineering for services and pipelines in Java, producing secure, high-quality production code; reviewing and debugging code written by others.
Architect and model data stores for fit-for-purpose needs across: Cassandra (partitioning, performance and consistency tradeoffs, resiliency patterns) and Oracle (schema design, SQL performance fundamentals, integration patterns)
Design service interfaces and integrations using REST and GraphQL, including clear API/error contracts, SLAs/SLOs, and backward-compatible change practices.
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.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s)/framework : Java, Kafka, Spark, Flink
Proven experience combining data architecture and solution engineering in large-scale, production environments.
Hands-on experience with: Kafka (design and implementation) , Publishing data to a lake / data platform (streaming and/or batch), Cassandra and Oracle and ava (services, pipelines, streaming/processing components)
Experience with schema registry / data contract design and governance.
Experience building APIs/integrations using REST and GraphQL.
Strong SDLC discipline (CI/CD, testing strategy, code review, production support mindset, observability).
Ability to work independently with little-to-no oversight; strong problem-solving and rapid learning ability
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.

Preferred qualifications, capabilities, and skills

Domain familiarity in Trust & Security areas such as fraud, IAM, device trust, cyber signals, third-party risk, and data loss prevention.
Experience with stream processing frameworks (e.g., Kafka Streams, Flink, Spark Streaming) and real-time enrichment/correlation patterns; nice to have: AI/ML concepts and feature store patterns (e.g., online/offline consistency, feature publishing/consumption).
Practical cloud-native experience (particularly AWS-based ecosystems) and platform modernization efforts.
Track record of driving reuse-first patterns and setting engineering standards across teams with no direct people management.
Experience with graph databases; TigerGraph preferred.

Base Pay/Salary: Jersey City,NJ $175,750.00-$260,000.00

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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