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 Clearwaters 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.