Software Engineer (Backend & AI)

Responsibilities:

• Design, build, and maintain efficient, reusable, and reliable Go code for high-traffic backend systems.
• Develop and support scalable microservices and APIs that power our core platform.
• Collaborate with product managers, designers, and other engineers to translate business requirements into technical specifications.
• Participate in the entire software development lifecycle, from ideation and design to deployment, monitoring, and operations.
• Write clean, well-tested, and documented code. 
• Identify bottlenecks and bugs and devise solutions to these problems.
• Help improve our code quality, development processes, and engineering standards.
• Contribute to system architecture discussions and technical decision-making.

• 2+ years of professional software development experience, with a focus on Go (Golang) and Python in a production environment.
• Solid understanding of Go paradigms, idioms, and common concurrency patterns (goroutines, channels).
• Proven experience in building and maintaining RESTful/gRPC APIs.
• Hands-on experience with relational databases (e.g., PostgreSQL) and/or NoSQL databases (e.g. Cassandra, MongoDB).
• Experience with containerization technologies, especially Docker.
• Experience in agentic coding tools like Claude Code or Codex.
• Familiarity with version control systems, preferably Git.
• A strong sense of ownership, a collaborative spirit, and excellent problem-solving skills.

• Experience with cloud platforms like AWS, GCP, or Azure.
• Knowledge of Kubernetes or other orchestration systems.
• Understanding DevOps principles and CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).
• Experience with message brokers (e.g. Apache Kafka, NATS).
• Familiarity with monitoring and observability tools (e.g., Prometheus, Grafana).
• Previous experience in microservices architecture.
• Knowledge on LLM and modern machine learning models
• Experience in prompt engineering
• Solid experience on vibe coding (produce maintainable and scalable code with LLM)
• Contributions to open-source projects or a public portfolio (GitHub, etc.).