Junior AI Pipeline Engineer

Primary Objective: Focus strictly on the “AI application layer” building prompt templates, tuning RAG (Retrieval-Augmented Generation) pipelines, managing local vector databases, and testing model inference engines.

Target Experience: 1–2+ years in Python development with hands-on GitHub/project experience in local LLMs and open-source AI frameworks.

Key Requirements & Core Competencies:

Python & Open-Source AI Stack:

Strong proficiency in Python and hands-on experience with modern AI orchestration frameworks: LangChain, LlamaIndex, or Haystack.

Familiarity with local model serving engines like vLLM, Ollama, or TGI (Text Generation Inference).

Prompt Engineering & NL-to-SQL Logic:

Demonstrated skill in writing, testing, and refining system prompts, specifically for T-SQL query generation, structured JSON output formatting, and context-grounded Q&A.

Understanding of guardrails to prevent hallucination and SQL injection (blocking DDL/DML execution).

RAG & Vector Database Management:

Hands-on knowledge of embedding models and local vector stores (PGVector, ChromaDB, or FAISS).

Experience chunking, indexing, and retrieving unstructured data (PDFs, clinical notes, medical docs) for context ingestion.

Model Quantization & Edge Optimization:

Basic understanding of model quantization formats (GGUF, AWQ, GPTQ) to run small-to-medium parameter models (3B, 8B, 14B like Qwen or Llama-3) on constrained hardware/VRAM footprints.

Pay: ₹500,000.00 - ₹800,000.00 per year

Benefits:

• Provident Fund

Work Location: In person