Kyzer Software - Artificial Intelligence Developer

Role

• Develop and deploy RAG systems to retrieve and generate contextually relevant responses using TypeScript and Node.js.
• Build conversational AI features, such as chatbots and virtual assistants, integrated into our web and mobile applications.
• Create and maintain TypeScript-based APIs (REST/GraphQL) to serve AI outputs to product teams.
• Integrate with vector databases (e.g., Pinecone, Weaviate) and cloud-based AI services (e.g., Hugging Face, AWS Bedrock) for RAG and conversational AI.
• Use libraries like TensorFlow.js or ONNX.js for client-side or server-side AI inference.
• Collaborate with team members to incorporate pre-trained models or embeddings into TypeScript applications, leveraging Python for model training or preprocessing when needed.
• Work with product teams to embed AI features into React-based front-ends or Node.js back-ends.
• Optimize AI features for performance, scalability, and user experience within our TypeScript ecosystem.
• Contribute to reusable TypeScript components and SDKs for seamless AI integration across Were Looking For : 4+ years of professional software development experience with TypeScript and JavaScript.
  

AI Knowledge :

Technical Skills

• Proficiency in TypeScript, Node.js, and front-end frameworks (e.g., React/NextJS).
• Experience with AI libraries like TensorFlow.js, ONNX.js, or similar for inference.
• Knowledge of REST/GraphQL APIs and integrating with cloud-based AI services (e.g., Hugging Face, AWS Bedrock).
• Familiarity with vector databases (e.g., Pinecone, Weaviate) or vector search Python Experience (Strong Plus) : Knowledge of Python for AI/ML tasks, such as model training, fine-tuning, or embedding generation using libraries like Hugging Face Transformers, Sentence Transformers, or Collaboration : Ability to work with team members to integrate pre-trained models or embeddings into TypeScript Problem-Solving : Strong ability to design and implement scalable AI-driven features within a TypeScript stack.
  

Nice To Have

• Experience with conversational AI frameworks (e.g., Botpress, Rasa) or RAG pipelines (e.g., LangChain, LlamaIndex).
• Experience with React/NextJS.
• Familiarity with exporting models to ONNX or TensorFlow.js formats.
• Knowledge of cloud platforms (e.g., AWS, GCP) for AI deployment.