Senior Lead Software Engineer -Java/AWS/Agentic

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 120,000 - 190,000; Full time

Job summary

JPMorganChase is seeking a Senior Lead Software Engineer in Columbus, OH to join the Employee Experience team. You will lead the design and delivery of scalable Java services, architect cloud-native solutions on AWS, and mentor engineers to raise quality and accelerate delivery.

You will build data pipelines with Databricks/Spark, implement secure SDLC practices, and drive AI-assisted development across teams while shaping technical strategies with product and design partners.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Advanced Java experience, building Spring Boot microservices in a distributed system.
• Experience with Java Core/EE, Spring Boot, Spring MVC and Spring Cloud.
• Proven track record delivering production system design, development, testing, and stability.
• Hands-on building cloud-native apps on AWS (compute, storage, DB, containers, serverless).
• CI/CD and modern build/version control practices (Git, Maven/Gradle).
• Automated testing with JUnit and mocks; strong quality-first mindset.
• Relational DBs with SQL and data modeling for high-throughput systems.
• Event streaming knowledge with Kafka and integration patterns.
• Experience leading enterprise AI-assisted development tools and responsible AI use.

Responsibilities

• Lead end-to-end design and delivery of scalable Java services and APIs.
• Architect cloud-native solutions on AWS with reliability and cost awareness.
• Mentor engineers through code reviews, design guidance, and standards.
• Collaborate with product/design/data to define technical strategies.
• Build data pipelines using Databricks and Apache Spark for analytics/ML workflows.
• Drive CI/CD, automated testing, and secure software development practices.
• Promote AI-assisted coding practices with measurable validation standards.
• Apply SDLC tooling knowledge to improve automation and quality.

Skills

Advanced Java

Spring Boot microservices

Cloud architecture AWS

CI/CD automation

Automated testing (JUnit)

SQL & relational databases

Kafka / messaging

AI-assisted development tooling

Secure coding practices

Data pipelines Databricks / Spark

Mentoring engineers

Agile / DevOps

Education

Formal training or certification on software engineering concepts

Tools

Git

Maven/Gradle

Docker

Kubernetes

Terraform / CloudFormation / AWS CDK

Jenkins / pipeline automation

Databricks

Apache Spark

Job description

As a Senior Lead Software Engineer at JPMorganChase within Employee Experience, you are an integral part of an agile team that enhances, builds, and delivers secure, stable, and scalable technology products. You will drive meaningful business outcomes by applying deep technical expertise, strong engineering judgment, and a customer‑focused mindset to solve complex problems across distributed systems, cloud, and artificial intelligence.

Job responsibilities

• Lead end‑to‑end design and delivery of scalable Java services and APIs, optimizing for performance, resiliency, and maintainability in production environments
• Architect and implement cloud‑native solutions on Amazon Web Services, applying well‑structured patterns for reliability, observability, and cost‑aware scalability
• Mentor engineers through thoughtful code reviews, design guidance, and pragmatic engineering standards that raise quality and accelerate delivery
• Collaborate with product, design, and data partners to define technical strategies that improve user experience and automate key workflows
• Build and optimize data pipelines using Databricks and Apache Spark to enable analytics and machine learning workflows at scale
• Drive engineering excellence across continuous integration and delivery, automated testing, and secure software development practices
• Drive 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.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Advanced Java experience, including building Spring Boot–based services in a microservices architecture
• Experience with Java (Core & EE, Spring Boot, Spring MVC, Spring Cloud)
• Practical experience delivering system design, application development, automated testing, and operational stability for production systems
• Hands‑on experience building cloud‑native applications on Amazon Web Services (e.g., compute, storage, database, container, and serverless services)
• Experience with continuous integration and delivery and modern build/version control practices (e.g., Git, Maven/Gradle, and pipeline automation)
• Proficiency with automated testing approaches and frameworks (e.g., JUnit and mocking frameworks) and a strong quality‑first mindset
• Experience with relational databases and SQL, including data modeling and performance considerations for high‑throughput systems
• Knowledge of messaging and integration patterns, including event streaming technologies such as Kafka
• 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

• Advanced Python experience for automation, data engineering, or machine learning enablement
• Experience building and deploying agentic or AI‑assisted workflows, including evaluation and human‑in‑the‑loop validation patterns
• Experience with infrastructure as code and cloud provisioning automation (e.g., Terraform, CloudFormation, or AWS CDK)
• Experience with containerization and orchestration (e.g., Docker and Kubernetes) for scalable service operations
• Experience with CockroachDB and Go (Golang) in distributed system environments