Lead Software Engineer, Java Microservices/API

JPMorganChase•Plano, TX

21h

About The Position

As a Lead Software Engineer at JPMorganChase within the Corporate Sector – Corporate Technology, you will contribute to an agile team that builds and enhances secure, stable, scalable technology products. You will lead the design, development, and delivery of cloud-native backend services and RESTful APIs, providing technical direction across the software development lifecycle—from architecture and implementation through testing, deployment, observability, and production support. The role focuses on Java, Spring Boot, microservices, AWS, Docker, and PostgreSQL. You will guide engineering quality and resilience, improve automation and operational stability, and support the adoption of enterprise-authorized AI-assisted engineering practices. You will set expectations for validating AI-generated outputs for correctness, security, performance, and responsible data handling. You will also work with internal stakeholders, vendors, and external partners on architecture, integration approaches, and technical feasibility, while contributing to engineering communities and continuous improvement initiatives.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Strong hands-on experience designing, developing, and maintaining enterprise-grade applications using Java and Spring Boot.
Demonstrated experience building and supporting RESTful APIs, microservices, and distributed service-oriented systems.
Practical cloud-native development experience, preferably with AWS, including ECS, containers, and cloud deployment patterns.
Experience leading effective use of approved AI-assisted software development tools, with the ability to set expectations for validating outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and security and resiliency expectations; experience coaching engineers on safe, compliant adoption.
Hands-on experience with Docker, containerized applications, and modern deployment practices.
Strong understanding of CI/CD pipelines, automated testing frameworks, release automation, and DevOps practices.
Solid PostgreSQL experience, including relational data modeling, query optimization, indexing strategies, and performance tuning.
Advanced understanding of the software development lifecycle, agile methodologies, application resiliency, observability, and secure software delivery.
Ability to lead technical design discussions, evaluate implementation options, and make sound engineering decisions for complex systems.
Experience reviewing code, mentoring engineers, and promoting engineering best practices across a team.
Strong analytical, debugging, and problem-solving skills, including diagnosing complex issues across application, infrastructure, and data layers.
Excellent communication and collaboration skills, with the ability to influence technical direction and work effectively with cross-functional stakeholders.

Nice To Haves

Experience with synchronous REST integration patterns for latency-sensitive credit or bureau calls, and event-driven or asynchronous processing using Kafka, Amazon SQS, or similar technologies.
Experience with dual-persistence patterns, such as Aurora PostgreSQL for transactional data and Snowflake for analytics and long-term audit.
Familiarity with API gateways, service mesh concepts, IDAnywhere or ADFS OAuth2 authentication and authorization patterns, edge-proxy vendor integrations, and API lifecycle management for third-party bureau integrations.
Experience with infrastructure-as-code tools such as Terraform (Atlas / TFE) or similar frameworks, and CI/CD delivery with blue/green deployments.
Hands-on experience with observability tools for logging, metrics, tracing, dashboards, and alerting, including Splunk, Dynatrace, CloudWatch, or Grafana, and production readiness for regulated, high-availability services.
Experience designing for high availability, fault tolerance, scalability, and operational resilience, including ECS NextGen cluster migrations, multi-AZ resiliency, and graceful degradation for downstream vendor outages.
Familiarity with performance and load testing and application tuning using BlazeMeter, JMeter, or similar tools for high-throughput, low-latency distributed systems under real-time credit-decisioning SLAs.
Experience with modern security practices, including secrets management (AWS Secrets Manager, Hera KMS, AppProtect), vulnerability remediation, dependency management, secure API design, and controls for 15-year audit retention and consumer credit data.
Experience leading technical modernization, platform migration, cloud adoption, or application resiliency initiatives in regulated environments.
Track record of contributing to engineering communities of practice, reusable frameworks, and technical standards, and mentoring engineers toward consistent, secure, and scalable delivery.

Responsibilities

Lead the design, development, and delivery of scalable, secure, cloud-native backend services and RESTful APIs using Java, Spring Boot, and microservices.
Provide technical leadership across architecture, solution design, coding standards, implementation, testing, deployment, observability, and production support.
Drive team adoption of enterprise-authorized AI-assisted engineering and automation practices, establishing standards for validating outputs for correctness, security, performance, and responsible data handling.
Produce high-quality production code, conduct code reviews, improve test coverage, and ensure compliance with secure coding and organizational engineering standards.
Design and implement resilient distributed systems that meet performance, scalability, availability, and maintainability requirements.
Develop and deploy cloud-native services on AWS, including use of ECS, Docker, and automated CI/CD practices.
Design, optimize, and maintain PostgreSQL data models, schemas, and queries, ensuring data integrity, performance, and scalability.
Produce and review architecture, technical design, and implementation artifacts for complex applications, aligned with enterprise architecture, security, and operational standards.
Identify recurring technical and operational issues and lead automation, remediation, and resiliency improvements to reduce toil and improve stability.
Lead technical evaluation sessions with internal stakeholders, vendors, and external partners to assess architecture, integration approaches, feasibility, and alignment with existing systems.
Analyze telemetry, operational data, quality metrics, and delivery patterns to identify trends and drive continuous improvement in engineering practices and reliability.
Contribute to engineering communities of practice and initiatives involving modern software engineering, cloud-native development, automation, AI-assisted delivery, and emerging technologies.
Coach engineers on safe, compliant use of AI-assisted development tools and promote engineering best practices across the team.