Top Software Engineer Jobs

Lead architecture and delivery of cloud-native, scalable platforms that support product intake, collaboration, content publishing, and developer tooling. Own end-to-end initiatives, design GraphQL/REST APIs and React UIs, integrate with Jira/SCM systems, ensure security/resiliency/observability, mentor engineers, and drive cross-platform standards and AI-assisted engineering practices to improve developer productivity and platform quality.

Lead design and delivery of scalable Java microservices and cloud-native AWS solutions. Mentor engineers, improve CI/CD and testing, build Databricks/Spark data pipelines, apply event-driven patterns (Kafka), and govern enterprise AI-assisted development practices to ensure secure, resilient, and cost-effective production systems.

Build and lead production Python software for technology-risk oversight, including data pipelines, PostgreSQL systems, authenticated APIs, and LLM agent workflows. Develop RAG, tool orchestration, evaluation, and guardrails; ensure security, auditability, observability, testing, reliability, and responsible AI use. Collaborate with Product, Risk, Controls, Compliance, and data teams while delivering dashboards and evidence packages.

Leads software engineering for JPMorganChase’s Payments technology organization. Designs, develops, tests, reviews, debugs, and operationalizes secure, scalable Java and cloud-native applications using microservices, Kafka, AWS, and PostgreSQL. Provides technical direction, serves as a subject matter expert, influences architecture and operations, and promotes enterprise software development practices. Drives responsible adoption and governance of AI-assisted engineering tools, including validation for correctness, performance, security, and compliance.

Leads full-stack software engineering across design, development, testing, troubleshooting, and operational stability. Builds secure production code using Java or Python and React, reviews peer code, and promotes AI-assisted engineering practices with secure validation standards. Drives automation, continuous delivery, application resiliency, cloud-native development, vendor evaluations, architectural improvements, and technical communities of practice within financial technology.

Leads software engineering within JPMorganChase’s CTO organization, designing, developing, testing, debugging, and supporting secure, scalable production systems. Builds advanced Java applications using AWS, Aurora, and PostgreSQL; improves application resiliency and operational stability; and guides teams in responsible AI-assisted development. Reviews code, drives automation, supports incident management, evaluates architectural solutions, and coaches engineers on secure, compliant AI tool adoption. Preferred experience includes Terraform, MyBatis, Node.js, modern frontends, and AI coding tools.

Lead design, development, testing, and maintenance of scalable Client Onboarding and KYC software. Drive CI/CD, code quality, documentation, Agile delivery, cross-functional collaboration, and responsible adoption of enterprise AI-assisted engineering practices.

Lead a global agile scrum team to design, build, and operate scalable, secure microservice-based applications. Integrate AI (Claude Code) into development and delivery, drive architecture and technical decisions, mentor engineers, enforce AI-assisted engineering governance, and ensure production quality, stability, and automation across the SDLC.

Leads strategy, architecture, governance, and engineering execution for a scalable UAT data provisioning platform. Builds workflow automation, self-service refresh capabilities, validation controls, and orchestration across multiple systems of record. Owns platform roadmaps, access management, auditability, reliability, operational readiness, incident response, and cross-team adoption of standardized engineering practices. Requires strong programming, API, distributed systems, cloud-native, CI/CD, and platform engineering expertise.

Leads design, development, testing, debugging, and operational stability for secure, scalable Java microservices using Spring and JPA. Reviews production code, automates recurring remediation, improves CI/CD and software delivery, and promotes enterprise-approved AI-assisted engineering practices. Evaluates architectures and vendors, leads technical communities of practice, and coaches teams on responsible, secure AI adoption and software engineering standards within financial services.

Leads development of secure, scalable software for a distributed multi-tenant platform, including APIs, data ingestion, pipelines, dashboards, and isolated AWS deployments. Designs and operates cloud-native Kubernetes workloads, promotes automation and AI-assisted engineering practices, and champions security, privacy, and supply-chain controls. Evaluates architectures, mentors teams, improves operational stability, and supports platform delivery across regulated environments.

Lead technical contributions on architecture and data solutions: design and build secure, high-quality Java/Spring production code, guide teams and vendors, adopt enterprise AI-assisted engineering practices, improve SDLC automation, support system design, testing, model hosting (XGBoost), and low-latency/high-throughput production support.

Lead design, develop, and deploy secure, scalable full-stack applications (Java or Python) for finance planning and analysis. Drive architecture reviews, operational stability, CI/CD automation, cloud-native AWS deployments, and integration of AI/ML/LLM capabilities. Mentor teams and lead engineering communities of practice.

Lead technical design, develop and deliver resilient backend services and automation pipelines. Write, review, and debug production-quality Java Spring Boot code, improve operational stability through automation, and drive architecture and delivery decisions within an agile team in a regulated enterprise environment.

Lead design and delivery of modern, responsive React/TypeScript UIs, architect micro-frontends, build reusable component libraries, prototype features, mentor developers, ensure accessibility and performance, and drive adoption of enterprise AI-assisted engineering practices.

Leads engineering for a regulatory and financial reporting platform. Designs scalable architecture and infrastructure, develops secure Python or Java applications, applies AI-assisted development and agent workflows, and supports deployment, monitoring, reliability, and operational stability. Partners with technology, product, and reporting stakeholders on data flows, controls, integrations, and reporting solutions. Requires strong cloud, DevOps, SQL, data modeling, and regulatory reporting expertise.

Lead development and operation of scalable ETL/data transformation pipelines using Spark and data lake technologies. Design, automate, monitor production workflows, improve cost and reliability, mentor junior engineers, and contribute to platform/SDK infrastructure and CI/CD while enforcing secure, AI-assisted engineering practices.

Leads software engineering within JPMorgan Chase’s Risk Technology team, designing, developing, testing, debugging, and operating secure, scalable applications. Reviews production code, automates recurring issue remediation, evaluates vendor and architectural solutions, promotes emerging technologies and AI adoption, and leads software engineering communities of practice. Requires strong Java and AWS experience, cloud-native development, CI/CD, agile methodologies, application resiliency, security, and financial-services technology knowledge.

Provides technical leadership for full-stack engineering across frontend, backend, APIs, databases, and AI integration. Builds secure, scalable AWS platforms and Spring Boot microservices, improves SDLC automation and CI/CD, modernizes technology risk and control frameworks, and governs responsible AI-assisted development. Leads code quality, testing, operational resilience, software supply-chain governance, and developer experience initiatives in a highly regulated enterprise environment.

Leads design, development, testing, troubleshooting, and operational stability for secure full-stack software solutions. Develops Java and Scala statistical algorithms, React-based applications, microservices, REST APIs, and cloud-native services using AWS, Hadoop, Databricks, and Kubernetes. Reviews code, improves automation and resiliency, performs unit and integration testing, and promotes responsible AI-assisted engineering practices, secure coding, and compliant validation across an agile team.

Lead technical development and modernization of a Software Defined Branch platform using C#, .NET, and PowerShell. Drive secure, production-grade code, AI-assisted engineering practices, Windows automation at scale, REST API and database integrations, and partner on architectural evaluations. Mentor peers, establish validation standards, and apply responsible AI and resiliency best practices within an agile delivery team.

Lead a globally distributed team to design, develop, and deliver resilient backend services and automation pipelines. Produce secure, high-quality Java Spring Boot code, troubleshoot systems, drive CI/CD and operational stability, and collaborate on architecture and product outcomes within a regulated enterprise.

Lead development of secure, scalable Java/Spring Boot applications on AWS; design architectures, produce artifacts, write and review code, enable CI/CD and monitoring, drive AI-assisted engineering practices, and improve operational stability.

Lead software engineering for secure, scalable, production-grade applications in an agile enterprise environment. Design complex solutions and architecture, develop Java microservices and REST APIs, improve reliability through automated testing and CI/CD, analyze system data, and build reusable components. Guide responsible adoption of AI-assisted engineering tools, coach team members on secure validation practices, troubleshoot complex issues, and deliver high-throughput distributed systems across cloud-native platforms.

Lead design, architecture, and delivery of full-stack, AI-enabled applications. Provide technical leadership across frontend, backend, APIs, databases, and AI integration. Drive engineering best practices, CI/CD, automated testing, cloud-native (AWS) solutions, and adoption of AI-assisted development while ensuring secure, resilient, scalable systems.