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Niche GenAI/LLM specialization reduces applicant density despite Bangalore location.
GenAI and LLMOps skills are transferable across industries but require specialized LLM and MLOps experience.
Strong mandatory GenAI, LLMOps, enterprise architecture skills and explicit years requirement increase shortlisting strictness.
End-to-end ownership and technical leadership for enterprise-scale Generative AI solutions, including architecture, platform strategy, and governance.
Design, deploy, and operate production-grade GenAI systems with focus on large language models (LLMs), retrieval-augmented generation (RAG), and LLMOps practices.
Act as a trusted technical advisor and mentor, translating business needs into AI strategies while ensuring compliance with security, scalability, and responsible AI standards.
6-9 years of experience in AI and machine learning with ownership of enterprise-scale generative AI solutions.
Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field.
Strong proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, Keras.
Location: Bangalore.
Experienced in architectural decision-making for GenAI solutions including model selection, deployment, and platform strategy.
Proficient in building and operationalizing scalable AI systems using MLOps/LLMOps, CI/CD, and monitoring practices.
Skilled in stakeholder communication and mentoring, capable of influencing cross-functional teams and driving GenAI adoption in enterprise environments.