Top Software Engineer Jobs

Lead backend engineer responsible for designing, building, and operating scalable, secure microservices for equities broker-dealer and prime finance platforms. Integrate AI/ML and GenAI (LLMs, RAG, embeddings, vector DBs) into production, drive architecture decisions, ensure SDLC and operational stability, mentor teams on responsible AI use, and collaborate with product and operations to deliver high-volume, low-latency financial systems.

Lead design and delivery of scalable, secure production software and reusable frameworks. Architect and govern agentic AI-enabled engineering workflows, advise cross-functional teams, drive adoption of AI-assisted SDLC practices, ensure validation, security, resiliency, and present technical recommendations to senior leaders. Apply cloud-native practices and improve automation at scale.

Lead design, development, and production support of secure, cloud-native data and analytics systems. Drive adoption of AI-assisted engineering practices, improve automation and resiliency, evaluate vendor solutions, and mentor teams on secure, scalable software delivery.

Lead back-end engineer responsible for designing, developing, and troubleshooting high-performance, latency-sensitive Java services. Drive adoption and safe validation of enterprise-authorized AI-assisted engineering practices, evaluate technical vendors, lead cross-team communities of practice, and promote secure, reusable patterns across distributed, cloud-native microservice architectures.

Lead software engineer responsible for designing, developing, and delivering secure, scalable Java/Spring Boot/React applications. Drives CI/CD, automation, operational stability, vendor evaluations, and engineering communities of practice.

Lead engineering efforts to design, build, and maintain AEM-based web applications; deliver secure, high-quality code; drive AI-assisted development adoption; integrate Adobe marketing tools; ensure resiliency, accessibility, SEO, and performance; automate recurring remediation; evaluate vendors and coach teams on responsible AI and security within financial services.

Lead design and implementation of a large-scale Marketing and Events data platform. Build and transform ETL on cloud/Databricks, ensure data quality, automate pipelines, enforce data standards, and deliver solutions using agile practices while mentoring and hiring team members and partnering with stakeholders.

Lead design, build, and maintain low-latency options algorithmic trading systems. Develop secure, high-quality production code, optimize performance, integrate market data and FIX protocols, apply AI-assisted engineering practices, mentor engineers, and collaborate with product to translate strategies into scalable algorithms while ensuring operational stability and observability.

Lead and deliver front-office desk workflow applications for commodities systematic trading: partner with traders, own end-to-end SDLC, implement front-to-back integrations across Athena and partner systems, apply AI-enabled spec-driven development, mentor engineers, set enterprise AI-assisted engineering practices, and ensure operational robustness, security, and measurable delivery outcomes.

Lead technical design and deliver secure, scalable C#/.NET software for trading systems. Drive architecture, coding, code review, automation, resiliency, CI/CD, and adoption of AI-assisted engineering practices while mentoring teams and engaging vendors.

Lead design and implement scalable Python-based systems for rates trading risk and PnL. Collaborate with quants, traders, and risk managers to build data pipelines, risk metrics, PnL attribution, and production-grade services. Participate in architecture, code reviews, and provide business support, including working on legacy systems.

Lead and coach full-stack teams building React-based web experiences and supporting APIs. Set technical direction, improve engineering quality, CI/CD and operational resilience, oversee API design, modernize delivery pipelines, and guide responsible adoption of enterprise AI-assisted development practices.

Lead and architect production-grade trading systems for Credit Pre-Trade Technology, build AI-native platforms, develop and maintain secure scalable code, partner with trading and product teams, drive AI-assisted engineering practices, support production stability and automation, and lead technical evaluations and communities of practice.

Lead design and delivery of large-scale, cloud-native, microservices-based systems on AWS for Corporate Treasury. Define engineering standards, drive DevOps and IaC adoption, build production-grade services (Python), architect AI-enabled solutions, resolve systemic risks, mentor senior engineers, and partner with stakeholders to translate complex business requirements into scalable, reliable, and secure technical solutions.

Lead and deliver secure, scalable Java/Spring applications on AWS; design, develop, troubleshoot, and improve operational stability. Drive adoption of AI-assisted engineering, review code, automate remediation, and evaluate vendor/architectural solutions.

Lead backend engineering efforts on an agile team: design, develop, test, and operate secure, resilient Java-based systems. Provide technical guidance, promote enterprise SDLC and AI-assisted development practices, drive automation/CI-CD, manage containerized deployments with Kubernetes, and influence engineering decisions across teams.

Lead development of cloud-native, microservices-based applications using Python backends and modern front-end frameworks. Design scalable, resilient systems on AWS/Azure/GCP, apply SDLC best practices, CI/CD automation, and enterprise AI-assisted engineering to improve code quality and delivery while mentoring teams and ensuring security and operational stability.

Lead full-stack engineering on cloud-native (AWS) systems for market and model risk. Design, develop, review, and operate secure production code, drive automation and CI/CD, adopt and validate AI-assisted engineering practices, improve resilience, and collaborate with product and regulatory stakeholders while mentoring teams and evaluating vendor solutions.

Lead design, development, testing, and production support for equities order management systems. Define architecture, build low-latency Java/J2EE services, REST APIs and event-driven messaging (JMS), ensure CI/CD, TDD, resiliency and security, collaborate globally, engage stakeholders, mentor engineers, and drive adoption of firmwide tools and best practices.

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.

Lead technical contributor on an agile Investment Banking engineering team. Design, develop, debug, and optimize secure production Java/J2EE/Spring Boot systems; drive adoption and validation of enterprise-approved AI-assisted engineering practices; lead vendor evaluations, automation and remediation efforts, and communities of practice; mentor engineers on responsible AI use and ensure test automation, performance tuning, and operational stability.

Lead development of secure, high-quality production software for analytics and credit risk; design, code (Python/Java), review, troubleshoot, automate remediation, drive CI/CD and cloud-native solutions, mentor junior engineers, evaluate vendors, and promote new technologies.

Lead hands-on development and mentor engineers to build secure, reliable data pipelines, APIs, and reporting for asset management. Own end-to-end delivery, participate in Agile ceremonies, drive automation, AI-assisted engineering practices, and improve operational stability.

Lead architecture and strategy for multiple banking products; design and deliver scalable, secure cloud-native production software; create reusable frameworks; influence cross-functional stakeholders; drive technical adoption and innovation; mentor teams and ensure operational stability and testing best practices.

Lead design, build, and operate scalable data platform components and pipelines (batch and real-time) using Spark, Flink, Kafka, Airflow and Databricks. Implement data modeling, governance, cataloging, observability, and production-grade code; partner with stakeholders and lead technical evaluations and communities of practice.