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Morgan Money has revolutionized liquidity trading across the firm serving our corporate clients in all regions to have next generation trading capabilities at their fingertips.

As a Java Lead Software Engineer at JPMorganChase within Asset & Wealth Management, you will help advance Morgan Money’s next-generation liquidity trading capabilities for corporate clients across regions. You will build resilient, secure, high-performing services and partner closely with investment and trading stakeholders to deliver measurable business outcomes. You will contribute to a fast-paced engineering culture with frequent production releases and help identify practical opportunities to apply AI and machine learning to improve reliability, insights, and client outcomes.

• Collaborate directly with investment teams, traders, and portfolio managers to translate objectives into durable technical solutions.
• Design and deliver high-quality backend services in Java with a focus on scalability, resiliency, and low-latency performance.
• Drive engineering decisions that shape product design, application functionality, and operational readiness.
• Lead delivery within an agile team, supporting frequent releases and continuous improvement based on business needs.
• Develop secure production code and review code changes to raise quality, maintainability, and reliability.
• Influence technology choices by evaluating and applying modern architectures, patterns, and tooling where they add clear value.
• Provide technical guidance to engineers and partner teams to accelerate delivery and reduce operational risk.
• Champion strong software development practices including automated testing, continuous integration, and continuous delivery.
• Improve observability and incident readiness by leveraging analytics and AI/ML techniques for anomaly detection, alert quality, and faster triage.

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Proficiency in Core Java and object-oriented design with strong problem-solving skills.
• Demonstrated experience applying test-driven development and behavior-driven development, including mocking frameworks and automated test suites.
• Hands‑on experience with inversion of control frameworks such as Spring or Guice.
• Experience with messaging and streaming technologies such as Kafka, IBM MQ, or Solace.
• Strong understanding of engineering fundamentals including continuous integration/continuous delivery, application resiliency, and secure coding practices.
• Proven ability to partner with cross-functional stakeholders and communicate complex technical topics clearly.
• Practical experience using data-driven methods (including applied AI/ML where appropriate) to improve decision-making, performance, or operational outcomes.

• Experience with cloud platforms and relevant certifications.
• Proficiency in Python for automation, data processing, or service development.
• Experience with digital assets technologies such as smart contracts, Ethereum, and digital wallets.
• Familiarity with responsible AI practices such as model evaluation, drift monitoring, and safe deployment patterns.