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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and deploy Generative AI solutions including LLMs and RAG architectures for operational and data science use cases.
Develop scalable AI/ML pipelines integrating structured and unstructured data, focusing on text classification and vector embeddings.
Integrate AI applications into enterprise systems ensuring performance evaluation, cost-efficiency, security, and responsible AI governance.
Minimum Requirements
Bachelor’s degree in Engineering, Statistics, Economics, Data Science, or related fields.
3–5 years of experience in analytics (operations, business, or product analytics preferred).
Strong programming skills in Python and hands-on experience with LLM frameworks (OpenAI, Azure OpenAI, Llama, Mistral, etc.).
Familiarity with deep learning frameworks (TensorFlow, PyTorch), RAG architectures, vector databases, and cloud deployment (Azure/AWS/GCP).
Ideal Candidate Profile
Experienced with prompt engineering and optimizing LLM interactions for real-world business applications.
Skilled in building end-to-end AI/ML solutions including orchestration frameworks like LangChain or LlamaIndex.
Able to collaborate effectively with business teams to translate use cases into functional AI systems integrated within enterprise workflows.