Software Engineer

Summary

Join Suvoda, a leader in e-clinical trial technology, as a C# Engineer to spearhead the development of a conversational assistant for our website. You will design, develop, and maintain this assistant, utilizing backend technologies like C#, Entity Framework, and SQL Server, and contributing to the front-end with React/TypeScript. Collaboration with the chief architect and VP of digital marketing is key. The ideal candidate possesses strong backend development experience with C#, Entity Framework, and SQL Server, along with front-end experience in React/TypeScript. Experience with MS Semantic Kernel or LLM-based conversational assistants is a plus. Suvoda offers a remote-first work environment.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or related field
• 3+ years of experience in backend development using C#, Entity Framework, and SQL Server
• Strong understanding of REST architecture and API development using C#
• Familiarity with API documentation tools like Swagger
• Experience in React/TypeScript or similar for front-end development
• Experience with version control (e.g., Git) and CI/CD pipelines

Responsibilities

• Develop & maintain backend systems using C#, EF, and SQL Server
• Design, implement, and document REST APIs / Swagger using best practices
• Develop or enhance a Javascript/Typescript front-end Chat component
• Design efficient data structures & queries to ensure high performance & scalability
• Implement intelligent conversational features using MS Semantic Kernel or other RAG/LLM frameworks to drive user engagement

Preferred Qualifications

• Experience with AWS
• Familiarity with containerization technologies like Docker or Kubernetes
• Understanding of web security practices and performance optimization techniques
• Strong communication skills and ability to work in a collaborative, remote-first environment
• Able to take direction, but also work in an independent manner towards a complex goal
• Knowledge of MS Semantic Kernel, Retrieval Augmented Generation (RAG), or agent-based LLM conversational assistants