CTS India

Mumbai, Maharashtra, India

AI Data Engineer LLM RAG (Senior)

Job ID JOB-005-0000241

Team: BIM-AI Core Reports to: SEM, BIM-AI Core

The models need to be deployed, the RAG index needs to work, and every project that runs through the platform should make the next one cheaper. This role owns the models, the data flywheel, and the fine-tuning that improves BoQ tolerance over time.

What you will do

• Deploy and operate DeepSeek R1 32B and Mistral Large 3 on the sovereign stack.
• Build the RAG pipeline over CTS DC project history — BoQ data, D&B rates, specifications.
• Run evaluation harnesses with the QA Lead: BoQ tolerance, layout quality, retrieval precision and recall.
• Lead supervised fine-tuning on CTS project data to get tolerance below ±8%.
• Make sure data sovereignty holds in practice, not just on paper.

Must have

• 5+ years in applied ML or data engineering, with at least 2 deploying LLMs in production.
• Hands-on with open-weight models (DeepSeek, Mistral, Llama) and inference stacks (vLLM, Ollama, TGI, llama.cpp).
• Solid RAG fundamentals: chunking strategies, embeddings, vector DBs, retrieval evaluation, re-ranking.
• Comfortable operating on-prem GPU hardware.

Nice to have

• Supervised fine-tuning (LoRA, QLoRA, or full fine-tune) on 30B+ models.
• AEC or construction background.
• DPDP Act or EU AI Act compliance experience.

Skills LLM deployment · RAG · Fine-tuning (LoRA/QLoRA) · vLLM / Ollama · Vector databases · Python · On-prem GPU

Role Details Models: DeepSeek R1 32B · Mistral Large 3 Stack: vLLM · Qdrant · Python Target: BoQ tolerance ±8% via supervised fine-tuning

Required Skills

Desired Skills