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Metro mid-level Bangalore role with 4–6 year band, but niche conversational LLM specialization reduces applicant pool.
Specialized conversational AI, LLM, and CMS experience required, limiting cross-industry transferability.
Multiple mandatory LLM, RAG, vector store, cloud deployment skills plus explicit 4–6 years makes screening strict.
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Translate ambiguous business needs into scoped AI requirements for content and media workflows by collaborating with product and content teams.
Prototype and deliver AI solutions rapidly for content tasks like drafting, summarization, taxonomy mapping, translation, and moderation, demonstrating within days.
Design, deploy, and manage production-grade architectures for large language models (LLMs) and multi-agent systems on cloud platforms with security, monitoring, and cost governance.
4 to 6 years experience including at least 2 years in content management systems within media or content-driven environments.
Strong hands-on expertise with commercial and open-weight LLMs, prompt engineering, retrieval augmented generation, and vector store integration.
Proficiency in Python programming, containerization, CI/CD pipelines, and cloud platforms (Azure, AWS, or GCP).
Bachelor's degree in Computer Science, IT, AI, or closely related field; Conversational AI or Cloud ML certifications preferred.
Experienced in designing and operating scalable, secure AI solutions for content/media workflows, including multi-agent orchestration and human-in-the-loop systems.
Skilled in rapid prototyping and iterative demonstration of AI use cases to cross-functional stakeholders.
Comfortable enforcing AI trust layers via guardrails, adversarial testing, and compliance measures in production environments.