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Tier-1 brand, metro location, popular GenAI role, and broad ML/DevOps requirements increase competition.
Highly specific GenAI/LLMOps skillset and deep ML experience reduces cross-industry transferability.
Explicit 7+ years plus specialized GenAI, LLM fine-tuning, vector DB, cloud and MLOps requirements raise strictness.
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Lead architecture and development of scalable AI backend systems focusing on Large Language Models, RAG, and Agentic workflows.
Build and deploy production-scale Agentic AI workflows and multi-model RAG pipelines, including model fine-tuning and prompt engineering.
Develop high-performance APIs and oversee MLOps practices like model versioning, monitoring, and CI/CD for AI services.
7+ years software development experience with at least 1-2 years in Generative AI or LLM integration.
Expert-level Python proficiency including asyncio, OOP, and build patterns.
Experience with AI frameworks such as Hugging Face, PyTorch, TensorFlow, and GenAI libraries like LangGraph or CrewAI.
Bachelor's or Master's degree in Computer Science, Engineering, or related STEM field.
Technical leader skilled at bridging AI research and scalable software engineering in production environments.
Experienced in cloud deployments (AWS, Azure, GCP), vector databases (Pinecone, Weaviate, FAISS), and DevOps tools (Docker, Kubernetes, CI/CD).
Proven mentor and code reviewer working in collaborative teams with strong focus on AI system robustness and performance.