HamburgerMenu
hirist

Rupeezy - Software Engineer - Gin Framework

Rupeezy
Others
1 - 4 Years
star-icon
4.2white-divider9+ Reviews

Posted on: 24/11/2025

Job Description

Description :



Requirements :



- Golang Expertise: Minimum 2 years of hands-on experience in Golang development.



- Database Management: Strong proficiency with SQL databases such as Postgres and MySQL.



- Cloud: Familiarity with AWS cloud services.



- Containerization: Knowledge of Kubernetes and Docker (preferred).



- Architecture and Scalability: Ability to contribute to system architecture, design scalable backend services, and ensure high reliability.



- API Development: Experience building REST APIs and working with frameworks like Go Gin and gRPC.



- CI/CD: Understanding of CI/CD pipelines and deployment processes.



- Monitoring and Logging: Proficiency with centralized logging tools, Grafana, dashboards, and observability.



- Concurrency: Strong understanding and implementation of concurrency patterns in Golang.



- Domain Experience: Fintech domain experience is a significant advantage.



- Education: Bachelor's degree in Computer Science, Engineering, or related field.



- Quality Focus: Knowledge of software development best practices and a commitment to producing high-quality code.



- Team Skills: Excellent problem-solving skills and the ability to work collaboratively in a team.



- Portfolio: Proven experience with a strong portfolio or demonstrable projects.



AI / ML (Good to Have) :



- Experience integrating LLM APIs (OpenAI, Anthropic, Gemini) into backend workflows.



- Understanding of embeddings, RAG (Retrieval-Augmented Generation), or semantic search.



- Familiarity with vector databases (Pinecone, Weaviate, OpenSearch KNN).



- Ability to build AI-assisted features such as search, summarization, automation, or recommendation systems.



- Exposure to fraud detection, risk scoring, or AI-driven insights (plus for fintech use cases).



- Basic understanding of Python for AI pipelines (preferred, not mandatory).



- Knowledge of MLOps basics, such as model deployment and monitoring (nice-to-have).


info-icon

Did you find something suspicious?