Senior Manager - RAG/LLM Specialist

About the Opportunity:

We are hiring RAG/LLM Specialists for a leading global analytics and AI consulting organization. You own the core mechanics of enterprise GenAI - designing, optimizing, and scaling retrieval pipelines and fine-tuned models from prototype to production.

Total Experience: 6-11 years

Key Responsibilities:

- Design and manage multi-stage RAG pipelines delivering low latency and high retrieval relevance.

- Drive fine-tuning initiatives (PEFT/LoRA) on open-source models for domain-specific performance.

- Build automated evaluation frameworks (RAGAS) to measure accuracy, context precision, and recall.

- Architect metadata filtering and hybrid search strategies in vector databases (Pinecone, Milvus).

- Write Python pipelines for document parsing, text chunking, and embedding generation.

- Systematically test and version-control prompts for reliable, repeatable model behaviour.

What Makes You a Fit:

- 3-7 years in ML/AI, software, or data engineering, including 1+ years hands-on with LLMs.

- Strong Python with PyTorch/TensorFlow, LangChain, LlamaIndex, and embedding models.

- Working knowledge of advanced RAG patterns (HyDE, parent-document retrieval) and prompt optimization.

- Hands-on experience with LLM APIs (OpenAI, Anthropic).

- Notice period: 30 days or less only.

- Education: Bachelor's/Master's in Computer Science, Data Science, or related field.

Why This Role:

You own the retrieval layer of enterprise AI - the difference between a demo and a system businesses run on. Level (Senior Analyst / Senior Manager) is mapped to your experience and depth.