Software Development Engineer

Job Summary

As a Software Development Engineer on the team, you will design, build, and operate distributed, microservices-based applications that power Clearwater's platform. You will write high-quality, well-tested code, solve complex problems with your teammates, and help mentor newer engineers. Success in this role requires strong problem-solving, clear communication, excellent coding ability, and a collaborative approach.

• Design, build, deploy, and maintain quality code that is simple, well-structured, clear, and well-tested.
• Break down and solve complex problems that require research or collaboration.
• Build and evolve microservices and APIs, with attention to performance, scalability, reliability, and security.
• Apply multiple levels of automated testing (unit, integration, contract, end-to-end).
• Initiate design and feature discussions, advocating for improvements in software quality.
• Coordinate with other teams to ensure successful integration of software applications.
• Troubleshoot and resolve production incidents quickly and effectively, and participate in on-call.
• Mentor new and less-experienced team members.
• Understand and address customer needs and issues with empathy and timeliness.
• Communicate effectively regardless of medium, audience, or timing.
• Perform other reasonable duties as required by management.

• Degree in computer science, engineering, or a related field.
• 4+ years of software development experience in Java or another typed, object-oriented backend language (e.g., Python, Go).
• Experience building services using microservices and distributed-system patterns (REST/gRPC APIs, messaging).
• Experience with a public cloud (AWS, Azure, or GCP), CI/CD, and production monitoring.
• Working knowledge of relational and/or NoSQL data stores.
• Strong command of automated testing and software engineering best practices.
• Strong analytical and problem-solving skills, with attention to detail.
• Clear written and verbal communication, and good documentation habits.
• Commitment to continuous learning, client satisfaction, and teamwork in a SaaS environment.

• Exposure to AI/ML or LLM-based features, or interest in applying AI to engineering workflows.
• Experience with containers and Kubernetes, or infrastructure as code (Terraform, CloudFormation).
• Experience with event streaming (Kafka, SQS, etc.) and observability tooling.
• Familiarity with financial services or investment data.