Senior GenAI Developer

Job Summary: We are looking for an experienced Senior GenAI Developer with deep expertise in Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, and building AI-driven applications. The ideal candidate will have strong backend development skills, particularly in Node.js, JavaScript, or TypeScript, and hands-on experience with language models (LLMs) and AI system deployment. Key Responsibilities: • Design and implement RAG architectures to build scalable AI applications that leverage external knowledge for improved response quality. • Develop, optimize, and experiment with AI prompts and prompt engineering techniques to enhance model accuracy and usability. • Fine-tune and integrate large language models (LLMs) into backend applications for customized AI functionality. • Build and maintain scalable, robust backend systems supporting AI features, using modern backend technologies. • Develop APIs and microservices for seamless integration of AI models and pipelines. • Optimize GenAI pipelines focusing on system performance, latency, and cost-efficiency. Required Skills & Qualifications: • Proven expertise in Prompt Engineering and AI prompt optimization strategies. • Strong understanding of RAG architecture and experience with LLM fine-tuning. • Proficiency in backend development using Node.js, JavaScript, or TypeScript. • Hands-on experience with AI model deployment, cloud AI services (e.g., AWS Sagemaker, Azure AI, Google AI), and API development. • Knowledge of Data Modeling, SQL, and building data pipelines to support AI workflows. • Familiarity with Vector Databases (e.g., Pinecone, Weaviate), Embeddings, and AI-driven search technologies. • Experience with MLOps, including CI/CD pipelines for AI models and performance tuning. • Strong problem-solving skills and ability to work in an agile development environment. Preferred: • Experience working in a startup or fast-paced AI/ML environment. • Knowledge of cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker). • Exposure to other AI/ML frameworks and tools such as TensorFlow, PyTorch, or Hugging Face.