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Tier-1 employer, mid-level (3–5 yrs) role, metro location and broad skillset increase applicant competition.
ML/AI and full-stack skills are moderately transferable across industries, but LLM/RAG specialization raises domain sensitivity.
Explicit 3–5 years, mandatory LLM/Generative AI, Python, cloud and RAG/vector DB requirements increase filter strictness.
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Design, build, and maintain Large Language Model (LLM) and Generative AI–based solutions including custom GPTs and domain-specific assistants.
Develop full stack AI-enabled applications integrating LLM capabilities with backend services, APIs, and UI, while supporting AI production workloads.
Implement prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and apply responsible AI principles and MLOps practices in cloud environments (Azure/AWS).
3–5 years of overall software engineering experience with a strong full stack development background.
Proficiency in Python and hands-on experience with LLMs, Generative AI, and prompt engineering.
Experience with RAG architectures, vector databases, and cloud platforms like Azure and AWS.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (minimum 15 years of formal education).
Experienced full stack developer who has transitioned into AI/ML with a focus on Generative AI and Large Language Models.
Capable of closely collaborating with onshore leads, offshore teams, and business stakeholders to deliver AI-powered applications.
Comfortable working in agile environments supporting MLOps workflows, DevOps, CI/CD, and production support for AI solutions.