Top Software Engineer Jobs in Singapore

Lead end-to-end software delivery for regulatory reporting systems within Payments Technology. Develop, review, debug, and optimize secure production code, data pipelines, and reporting workloads using Python, PySpark, Spark, and Databricks. Establish AI-assisted engineering practices, validation standards, automation, and SDLC governance. Partner with stakeholders on data quality, lineage, reconciliation, and audit controls while providing technical direction and serving as a subject matter expert.

Develops secure, scalable software within an agile Corporate and Investment Banking team. Responsibilities include designing, coding, testing, troubleshooting, and maintaining applications; analyzing data; applying SDLC, CI/CD, resiliency, and security practices; and using authorized AI-assisted development tools while validating outputs. Requires 2+ years of software engineering experience, a relevant bachelor’s degree, programming and database-querying skills, and experience across the software development lifecycle.

Designs, develops, tests, troubleshoots, and maintains secure, scalable Python software for JPMorgan Chase’s Athena Risk Team. Creates architecture and design artifacts, analyzes large datasets, improves application stability, and delivers production code within an agile environment. Collaborates across technical and business domains while applying software development lifecycle, resiliency, security, and continuous integration practices.

Develops, tests, reviews, and troubleshoots secure, scalable Java software within an agile Payments Technology team. Designs high-throughput distributed systems, improves application resiliency and operational stability, automates recurring remediation, and applies CI/CD and secure engineering practices. Uses and guides responsible adoption of AI-assisted development tools, contributes to technical communities, and supports end users. Works with relational and NoSQL databases and on-premises or public cloud environments.

Lead design and deliver high-quality, secure Java-based microservices and web applications. Drive architecture reviews, operational stability, CI/CD automation, and adoption/governance of AI-assisted engineering practices while mentoring engineers and promoting reuse and secure SDLC standards.

Leads end-to-end software engineering for regulatory reporting initiatives in payments technology. Builds secure, scalable Java and Python applications and Databricks/Spark data pipelines with quality, lineage, and reconciliation controls. Guides architecture, code reviews, automation, operational stability, and AI-assisted engineering adoption. Partners with vendors and internal teams while coaching engineers on secure, responsible AI practices and modern software delivery.

Provides production support for FX and Commodities trading applications, troubleshooting complex business and infrastructure issues while minimizing downtime. Develops secure Python software, monitoring tools, automation, helper APIs, and AI-assisted solutions across on-premises and AWS cloud environments. Supports trade floor users, improves operational workflows, manages onboarding and infrastructure upgrade projects, and contributes to resiliency management, observability, and continuous application improvement.

Develop and deploy Java microservices for Trading Technology using reactive programming, Kafka, IBM MQ, Kubernetes, Redis, and AWS. Contribute to API and domain-driven design, testing, code reviews, scalability validation, monitoring, security, and technical documentation. Apply CI/CD, DevOps, TDD/BDD, distributed systems, and enterprise-approved AI-assisted development practices while supporting secure, scalable, event-driven applications.

Develops secure, scalable full-stack and back-end software for JPMorganChase’s Global Portfolio Holdings Technology team. Responsibilities include designing and troubleshooting applications, producing architecture artifacts, implementing Java and Python solutions, collaborating across globally distributed Agile teams, and maintaining automated testing, CI/CD, monitoring, and operational reliability. The role also applies AI-assisted development tools responsibly, analyzes application data, and guides improvements to software quality, architecture, security, and resiliency.

Build high-performance research and production systems for AI-driven systematic trading. Responsibilities include developing low-latency C++ services, market-data and execution components, quantitative research pipelines, backtesting and simulation platforms, machine-learning model deployment workflows, and monitoring infrastructure. Optimize systems for throughput, latency, memory efficiency, resilience, and deterministic behavior while partnering with quantitative researchers and traders to productionize strategies and support live trading systems.