What We Offer:

• Canteen Subsidy
• Night Shift allowance as per process
• Health Insurance
• Tuition Reimbursement
• Work-Life Balance Initiatives
• Rewards & Recognition

What You’ll Be Doing:

• Design, build, and deploy LLM-driven applications (e.g., document summarization, RAG-based QA, chatbots). 
• Work with open-source LLMs using platforms like Ollama and Hugging Face. 
• Implement Lang Chain and Lang Graph workflows for multi-step, multi-agent task resolution. 
• Build and optimize RAG (Retrieval-Augmented Generation) systems using vector databases. 
• Collaborate with cross-functional teams to ship features to production. 
• Stay up to date with the latest in open-source LLMs, model optimization (LoRA, quantization), and multi-modal AI. 

What We Expect You To Have:

• 3–5 years of hands-on experience in AI/ML engineering. 
• Proficient in Python, PyTorch, and Hugging Face Transformers. 
• Proven experience with Lang Chain and Lang Graph for LLM workflows. 
• Familiarity with Ollama, Mistral, LLaMA, or similar open-source LLMs. 
• Experience working with vector stores (Qdrant, Pinecone, Weaviate, FAISS). 
• Skilled in backend integration using FastAPI, Docker, and cloud platforms. 
• Solid grasp of NLP, LLM reasoning, prompt engineering, and document parsing. 
• Experience with LangServe, OpenAI tool/function calling, or agent orchestration. 
• Background in multi-modal AI (e.g., image + text analysis). 
• Familiarity with MLOps tools (MLflow, Weights & Biases, Airflow). 
• Contributions to open-source GenAI projects. 
• Understanding LLM safety, security, and alignment principles.