Back
Tier-1 brand and metro boost competition, but niche GenAI/RAG/agentic skillset narrows candidate pool.
High because role demands specialized GenAI, RAG, agentic AI and architecture experience not broadly transferable.
High because explicit 5+ years plus mandatory GenAI, RAG, vector DB, cloud, and leadership requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead architecture and delivery of enterprise-scale AI solutions using LLMs, multimodal models, RAG pipelines, and Agentic AI frameworks.
Define AI architecture standards and scalability strategies, including cloud integration and model deployment with cost estimation and monitoring.
Manage and mentor AI and engineering teams while collaborating with senior stakeholders to align AI solutions with business goals and compliance requirements.
5+ years of AI/ML development experience with at least 3+ years in Generative AI and Agentic AI systems.
Expert proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow, Hugging Face) and usage of FastAPI.
Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
Experience designing scalable AI architectures and working with cloud services (AWS, Azure, GCP).
Experienced AI architect with strong background in generative models, RAG, and agent orchestration frameworks (e.g., LangChain, AutoGen).
Proven ability to lead large teams and deliver enterprise-grade AI projects from conceptualization through deployment and monitoring.
Skilled in integrating AI solutions with cloud infrastructure, cost optimization, security, and governance considerations.