Senior Software Engineer

Develop and maintain microservices primarily using Golang, with a focus on reliability and resilience.

• Design, build, debug, and enhance features; improve performance and resolve bugs iteratively.
• Containerize services for deployment on Kubernetes (k8s) environments using Helm charts.
• Gain and apply a comprehensive understanding of end-to-end technical architecture and dependencies.
• Write high-coverage tests, including unit, contract, end-to-end, and integration tests.
• Manage code with Git and utilize CI/CD pipelines for building, testing, and deployment.
• Build, test, and deploy remotely to various environments, including local and lower-level environments.
• Review and improve team members’ code for performance, readability, and correctness; contribute to code design and process discussions.
• Report status updates and manage risks for assigned applications/services.
• Participate in demos and acceptance discussions with cross-functional teams (analysts, developers, product owners).
• Assist with task planning, estimation, and sprint-based workflow activities.
• Take ownership of delivery tasks including design, development, testing, deployment, configuration, and documentation to meet business requirements.

Work collaboratively in a team environment with a strong focus on delivering solutions for real-world problems.

• Demonstrate proficiency in Python/Golang and SQL in production settings, with a willingness to learn new technologies.
• Experience with large data volumes, high throughput, and low latency systems.
• Familiarity with modern service design, containers, orchestration, streaming platforms, APIs, and in-memory/NoSQL stores.
• Comfortable in a DevOps-driven workflow, including CI/CD and evolving development processes.
• Communicate effectively with a range of technical and non-technical stakeholders.
• Adhere to best practices in code review, version control, and change control, especially in scale-up environments.
• Experience optimizing solutions within technology constraints.
• Interest or experience in deploying machine learning technologies to production.