Generative AI Engineer

EXL; Gurugram District; Hybrid; INR 1,500,000 - 2,500,000; Full time

Job summary

A leading technology solutions provider is seeking a Generative AI Engineer with 5-12 years of experience in Machine Learning. The candidate should have strong fundamentals in statistical modeling, core NLP concepts, and transformer architectures. Responsibilities include building and deploying GenAI solutions, optimizing LLM usage, and understanding retrieval-augmented generation strategies. The role offers flexibility with a location in Gurugram or remote options.

Qualifications

• 5-12 years of experience in Machine Learning.
• Intermediate knowledge of classical statistical modeling.
• Experience in deploying prototypes to cloud environments.

Skills

Statistical & ML Fundamentals

Core NLP concepts

Transformer architectures

Understanding LLM capabilities

Prompting Engineering

RAG pipeline understanding

Deployment to cloud environments

Job description

We are looking for a Generative AI Engineer with strong fundamentals in Machine Learning, and hands on experience in building and deploying GenAI solutions.

Location: Gurugram / Remote

Experience: 5-12 years

Must Have skills

• Statistical & ML Fundamentals : Intermediate experience with classical statistical modeling
• Core NLP concepts and tokenization
• Transformer architectures, attention, and encoder–decoder models
• Understanding LLM capabilities, limitations, and use‑case fit
• LLM selection and evaluation(LLM, non-LLM) approaches
• Cost, token, and context optimization considerations
• Prompting Engineering
• Prompting strategies, trade‑offs and use cases
• Guardrails to reduce hallucinations
• RAG (Retrieval-Augmented Generation)
• End‑to‑end understanding and chunking strategies
• RAG pipeline understanding and steps involved
• Vector search and retrieval concepts
• Evaluation of RAG outputs; non LLM based evaluation approaches
• Experience deploying prototypes to cloud environments
• Techniques for handling high-volume requests and scaling

Good to Have skills

• Feedback loops to improve model performance and accuracy
• Exposure to speech-to-text / voice-based pipelines