Top Software Engineer Jobs

Leads software engineering efforts for a data platform within an agile corporate technology team. Designs, develops, tests, debugs, and maintains secure, scalable production systems; reviews code; improves operational stability through automation; and promotes responsible AI-assisted development practices. Evaluates vendors and architectural solutions, coaches engineers on secure AI use, and applies cloud-native technologies, software development lifecycle practices, resiliency, and security standards in financial services systems.

Lead development of a proprietary Java and Spring Boot platform framework used by more than 1,000 application teams. Own framework design, versioning, compatibility, testing, containerized delivery, shared platform integration, and complex issue resolution. Lead system design discussions, code reviews, AI-assisted engineering adoption, and geographically distributed collaboration. Mentor engineers and guide architectural decisions affecting large-scale cloud-native applications.

Leads engineering delivery for Chase Business web applications in an agile environment. Designs and maintains responsive, accessible, high-performance user interfaces using React, JavaScript, and TypeScript. Builds scalable single-page applications, testing strategies, REST integrations, and front-end architectures. Establishes software development best practices, improves Jenkins-based workflows and pipelines, collaborates with product and design partners, and ensures adherence to architecture, security, and risk standards. Reviews enterprise-authorized AI-assisted coding outputs for quality and security.

Lead full-stack software engineering initiatives using Java, Spring Boot, React, and AWS. Design and deliver secure, scalable services and web applications, create architecture artifacts, troubleshoot production issues, improve automation and observability, and lead technical design decisions. Mentor team members, guide responsible use of AI-assisted development tools, analyze application data, and improve operational stability, resiliency, and coding practices within an agile financial-services environment.

Leads software and infrastructure engineering for a network test automation platform. Provides technical direction, architects scalable changes, and drives complex programs across cloud, on-premises, data center, operating system, hypervisor, and networking environments. Establishes AI-assisted engineering governance, secure validation practices, automation standards, observability, telemetry, and CI/CD improvements. Collaborates with technical teams, vendors, and other platforms to modernize infrastructure, mitigate risk, and promote reusable engineering frameworks.

Lead software engineering delivery of secure, scalable, cloud-native microservices applications. Design and develop production code, review and debug others’ work, resolve technical issues, improve application resiliency, automate recurring remediation, and support zero-downtime releases. Collaborate within agile teams, apply domain modeling and modern architectural patterns, lead technical communities of practice, mentor others, and drive adoption of effective engineering practices.

Lead and support database modernization, design, performance tuning, migrations, and production troubleshooting. Serve as a subject-matter expert advising application teams, partnering with PaaS/DBaaS/cloud teams, driving adoption of AI-assisted engineering practices, automation and CI/CD, and creating modernization patterns and tools to accelerate delivery and ensure resilience, security, and cost optimization.

Leads full-stack software engineering within an agile Asset Management team. Develops, reviews, tests, debugs, and operationalizes secure production code using Java, Python, AWS, Spring JPA, Hibernate, PostgreSQL, REST, and GraphQL. Drives adoption and governance of AI-assisted engineering practices, validates AI outputs, mentors technical teams, influences architecture and product decisions, and promotes SDLC automation, reusable frameworks, scalability, resiliency, and security.

Lead design, development, testing, and maintenance of scalable Client Onboarding and KYC software. Collaborate cross-functionally, implement CI/CD, apply OOP and design patterns, drive code quality and documentation, adopt enterprise AI-assisted engineering practices, and coach teams on responsible AI usage.

Leads development of secure, scalable native mobile applications within an agile engineering team. Responsibilities include designing and reviewing production code, troubleshooting technical issues, mentoring engineers, applying AI-assisted development practices responsibly, improving automation and application resiliency, maintaining CI/CD pipelines, and evaluating vendor and architectural solutions. The role emphasizes Android development with Kotlin alongside knowledge of iOS technologies, mobile architectures, testing frameworks, REST services, and secure software engineering.

Leads development of secure, scalable, cloud-native microservices and full-stack applications. Designs resilient architectures, writes and reviews production code, troubleshoots issues, and improves operational stability. Drives automation, continuous delivery, AI-assisted engineering practices, responsible AI usage, and software development standards. Mentors engineers, leads communities of practice, adopts modern technologies, and delivers reliable solutions across distributed systems, APIs, databases, and web technologies.

Principal Software Engineer responsible for designing scalable software frameworks and secure production code, governing enterprise Databricks platforms, and leading agentic AI-enabled engineering workflows. The role advises cross-functional teams, establishes responsible AI, security, resiliency, and governance standards, manages competing portfolios, and influences senior stakeholders. It requires deep expertise in Python, AWS, Terraform, Databricks architecture and operations, enterprise data platforms, and global data governance.

Leads software engineering for the Control-M orchestration platform, providing technical direction, developing and reviewing secure production code, and improving system design, functionality, operations, and stability. Drives responsible adoption of AI-assisted engineering practices, automation, governance, testing, and secure coding standards. Serves as a subject matter expert, supports enterprise frameworks, and collaborates with distributed teams, vendors, and stakeholders to modernize large-scale technology products.

Leads development of secure, scalable backend services and APIs using Java, Spring Boot, microservices, AWS, and cloud-native technologies. Designs infrastructure with Terraform, manages containerized applications, builds event-streaming solutions, and works with relational and NoSQL databases. Drives code quality, automation, observability, SRE practices, remediation of recurring issues, and responsible use of AI-assisted engineering tools. Evaluates vendor and internal architectural solutions while reviewing and troubleshooting production code.

Designs scalable software frameworks and production systems for high-performance computing, optimizing AI/ML model training and inference across compute architectures. Leads technical design reviews, benchmarking, telemetry, secure coding, and operational improvements. Develops enterprise agentic AI engineering workflows with governance, validation, auditability, security, and resiliency guardrails. Mentors engineers and drives adoption of HPC, AI/ML, and automation practices across teams.

Leads software engineering within JPMorganChase’s Payments organization, designing, developing, testing, and troubleshooting secure, scalable production systems. The role creates architecture and design artifacts, maintains algorithms, analyzes large datasets, improves system architecture and coding practices, and uses enterprise-approved AI-assisted development tools responsibly. Required experience includes Java, Python, SQL, PostgreSQL, AWS, SDLC, agile methods, CI/CD, resiliency, and security. Databricks and machine learning frameworks are preferred.

Hands-on lead developer responsible for designing, building, and operating cloud-native, secure, high-quality software. Drives engineering standards, mentors peers, adopts approved AI-assisted tools responsibly, automates remediation, and leads vendor/architecture evaluations.

Leads full-stack software engineering within an agile finance technology team. Develops, reviews, debugs, and governs secure production code; drives AI-assisted engineering, automation, monitoring, and operational stability. Provides technical guidance, coaches engineers, evaluates vendor architectures, collaborates with product teams, manages delivery risks, and leads engineering communities of practice. Requires extensive enterprise software development experience across Java, Spring, JavaScript, React, testing, CI/CD, security, event-driven systems, and observability technologies.

Leads a team of software engineers in designing, developing, testing, and operating secure, resilient Java microservices. Oversees architecture, implementation, technical troubleshooting, and design documentation for event-driven systems using Kafka, Spring Boot, and cloud infrastructure. Promotes automation, responsible AI-assisted development, secure coding, continuous delivery, operational stability, and adoption of emerging technologies. Provides technical leadership across agile teams and evaluates architectural solutions with vendors and internal stakeholders.

Lead software engineering for JPMorganChase’s Corporate Data and Analytics Services team. Design, develop, test, troubleshoot, secure, and maintain scalable production systems using Java, Python, AWS, and agile SDLC practices. Review code, improve resiliency and automation, remediate recurring issues, and promote responsible AI-assisted engineering practices. Lead architectural evaluation sessions with vendors and internal teams while coaching engineers on secure, compliant AI tool adoption.

Lead development of secure, scalable full-stack applications for JPMorgan Chase’s Asset and Wealth Management client services platform. Responsibilities include Java, Spring, React, cloud architecture on AWS, SQL and Snowflake data solutions, testing, deployment, operational stability, and system modernization. The role leads AI-assisted engineering practices, collaborates with product owners and global stakeholders, supports agile delivery, and serves as a primary technical and product contact.

Leads development of secure, scalable Java and AWS software systems, including microservices, event-driven platforms, and production machine-learning systems. Designs data and feature pipelines, model deployment and monitoring, automation, CI/CD, and operational stability practices. Guides code reviews, testing, secure coding, vendor evaluations, and responsible adoption of AI-assisted engineering tools. Collaborates across product, data, platform, SRE, and governance teams while promoting MLOps, LLM, observability, and model-monitoring practices.

Leads software engineering for private cloud and next-generation infrastructure. Provides technical direction, develops and reviews secure production code, solves complex design and functionality problems, and improves SDLC automation through approved AI-assisted engineering practices. Establishes validation, security, testing, and governance standards; supports cloud infrastructure and APIs; influences product and operational decisions; and serves as a subject-matter expert and engineering community advocate.

Lead software engineer responsible for designing, building, and operating secure, high-quality Python-based production systems. Drive distributed systems design, automation, AI-assisted engineering adoption, troubleshooting, mentoring, and cross-functional collaboration to improve reliability and delivery.

Leads the design and development of secure, scalable software frameworks and production systems. Builds reusable engineering platforms, reviews code, improves SDLC automation, and governs agentic AI-enabled development workflows with responsible AI, security, resiliency, auditability, and human-in-the-loop controls. Advises cross-functional teams, solves complex technical problems, promotes cloud-native practices, and influences senior technology and business leaders.