- Collaborate with cross-functional teams to understand business needs and translate them into backend functionalities for GenAI and Agentic AI projects.
- Proficient with LLM interaction frameworks like LangChain, Semantic Kernel, and LlamaIndex, and experienced in integrating, scaling, and deploying GenAI and agentic applications in production.
- Skilled in setting up data pipelines for both model training and real-time inference to support AI workloads efficiently.
- Advanced Python expertise including OOP, asynchronous programming (asyncio), concurrency (multithreading, multiprocessing), design patterns, memory management, and performance optimization for scalable GenAI systems.
- Solid foundation in data structures, algorithms, software design principles (SOLID, clean architecture), and hands-on experience with cloud-native development on Azure/AWS, including serverless, microservices, and container orchestration (Kubernetes, Docker).
- Experience with additional OOP languages (Java, C++, C#) and familiarity with WebSocket implementations for real-time application functionality.