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Known employer, metro Bengaluru, mid-level AI role, and popular LLM skillset increase candidate competition.
Requires production LLM, RAG, MCP, and cloud AI platform experience, limiting cross-industry transferability.
Multiple mandatory filters: explicit years, production LLM experience, MCP, RAG, AWS, and specific frameworks.
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Own end-to-end lifecycle of LLM-powered applications and AI-driven features including design, deployment, evaluation, monitoring, and continuous optimization.
Design, develop, and deploy production-grade LLM, multimodal AI, and generative AI solutions ensuring scalability, reliability, security, and performance.
Integrate AI models and Retrieval-Augmented Generation (RAG) pipelines into enterprise applications and backend services, driving measurable business impact.
5-7 years of software engineering experience including 2-3 years in designing, deploying, and operating AI/ML solutions in production environments.
Strong proficiency in Python and software engineering fundamentals; mandatory proficiency in Postgres SQL.
Hands-on experience with Large Language Models (LLMs), generative AI technologies including RAG, prompt engineering, and integration of AI agents.
Experience working with cloud-native AI platforms, preferably AWS (e.g., Bedrock, SageMaker).
Demonstrates ability to translate business requirements into scalable, production-ready AI solutions within enterprise environments.
Experience managing complex, multi-component AI systems with high ownership and accountability.
Proficient in modern AI/ML frameworks and orchestration tools such as PyTorch, LangChain, and familiarity with model context protocols (MCP).