AI Architecture & LLM Implementation:

• Lead the architecture, design, and development of enterprise AI/LLM applications.
• Design and implement production-ready RAG (Retrieval-Augmented Generation) systems with high accuracy and low latency.
• Develop and optimize LLM workflows using frameworks such as LangChain and LlamaIndex.
• Build and maintain scalable vector database solutions using Milvus, Pinecone, or Weaviate.

Backend & Data Engineering:

• Develop high-performance backend APIs using Python, FastAPI, and Django.
• Implement asynchronous programming techniques for scalable microservices.
• Design real-time and batch data pipelines using Apache Kafka, Apache Airflow, or equivalent technologies.

Security & Cloud Architecture:

• Design secure cloud-native architectures following industry security best practices.
• Implement OAuth2 authentication, encryption standards, and secure API integrations.

Advanced NLP & Research:

• Solve complex NLP challenges including sarcasm detection, contextual understanding, bias mitigation, and text classification improvements.
• Evaluate emerging AI technologies and recommend improvements to enhance product capabilities.

Leadership & Collaboration:

• Mentor software engineers and establish engineering best practices, code quality standards, and architectural guidelines.
• Collaborate with product managers, data scientists, DevOps engineers, and cross-functional teams.