Detailed JD
• Generative AI & LLM expertise — building applications using LLMs, prompt engineering, and retrieval-based architectures (RAG)
• Agentic AI capabilities — designing AI systems that can automate workflows, make decisions, and integrate with tools/APIs
• Strong software engineering skills — especially Python and Java, with experience building APIs and microservices
• Cloud-native development — particularly deploying and scaling AI solutions in AWS environments
• Data engineering foundations — working with large datasets, pipelines, and tools like Spark to support AI models
• MLOps / AI deployment — taking models from development to production, including monitoring and scaling
• System integration — embedding AI into existing enterprise platforms and workflows