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Strong employer brand, Bangalore metro, mid-level AI title and broad GenAI demand increase competition.
Core AI engineering skills transfer across industries, but enterprise governance and agentic AI needs add specificity.
Mandatory years, leadership, and specific GenAI/RAG/architecture skills create strict shortlisting filters.
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Lead design and architecture of enterprise-scale AI solutions using LLMs, multimodal models, and advanced Generative AI techniques.
Oversee development and deployment of Retrieval-Augmented Generation (RAG) pipelines and Agentic AI frameworks including MVPs and proof-of-concepts.
Manage AI & engineering teams, define architecture standards, and ensure alignment with business objectives and AI governance compliance.
Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
Minimum 5 years of AI/ML development experience, including 3+ years in Generative AI and Agentic AI systems.
Expert proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face), plus experience with FastAPI.
Strong knowledge of RAG pipelines, Agentic AI frameworks (e.g., LangChain, AutoGen), vector databases (FAISS, Pinecone), and cloud services (AWS, Azure, GCP).
Experienced in architecting scalable AI solutions and leading large teams delivering enterprise-grade AI projects.
Technical leader comfortable with end-to-end AI system design including model deployment, cost estimation, monitoring, and security governance.
Demonstrated ability to create rapid prototypes (MVPs) and influence technology strategy with senior stakeholders in complex environments.