Data Scientist/AI Engineer - LLM/Generative AI

About the Role :

This is a delivery-focused role, where the expectation is that you have experience working on LLM-based applications beyond the prototype stage and understand how to successfully deploy AI systems into production environments.

You will work on high-scale data systems, production ML pipelines, and GenAI-powered applications, contributing to analytics and intelligent product features.

Key Responsibilities :

- Design, develop, and deploy LLM-based and GenAI solutions for real-world use cases

- Build RAG pipelines, LLM workflows, and AI-powered assistants

- Perform prompt engineering, model evaluation, and fine-tuning

- Develop and optimise advanced machine learning models for prediction and analytics

- Work with large-scale structured and unstructured datasets

- Build scalable inference systems and APIs for model deployment

- Integrate AI/ML solutions with existing products and data platforms

- Improve model performance, latency, and cost efficiency

- Collaborate closely with engineering and product teams to productionize AI features

- Monitor, evaluate, and continuously improve deployed models

What Were Looking For :

- Hands-on experience in building LLM and Generative AI applications

- Expertise in prompt engineering, RAG architectures, embeddings, and vector search

- Experience with frameworks such as LangChain, LlamaIndex, or similar tools

- Familiarity with vector databases like FAISS, Milvus, or Pinecone

- Practical experience with PyTorch or TensorFlow

- Experience working with large-scale and distributed datasets

- Proven experience in deploying ML/AI models as APIs or production services

- Strong SQL and data analysis skills

- Understanding of ML lifecycle, evaluation, and monitoring

- Exposure to MLOps practices and experiment tracking tools

- Experience with cloud platforms (AWS/GCP/Azure) is preferred

- Familiarity with streaming or high-volume telemetry data systems is an added advantage

Ideal Candidate Profile :

- Has successfully deployed at least one LLM/GenAI solution in production

- Demonstrates a strong problem-solving and execution mindset

- Comfortable working in fast-paced, ambiguous environments

- Focused on scalable, practical AI solutions rather than just experimentation

- Able to translate business problems into effective AI-driven solutions

- Strong communication and collaboration skills