AI Engineer – LLM / RAG / Agentic AI | Remote | 3+ Years We’re Hiring: AI Engineer

We are looking for an experienced AI Engineer with robust hands-on expertise in LLMs, RAG, Agentic AI, Python, vector databases, and document intelligence.

The ideal candidate will have experience building production-ready Generative AI applications, implementing LLM agents and retrieval pipelines, processing complex documents, and deploying AI solutions to cloud environments.

Job Details

Role: AI Engineer – LLM / RAG / Agentic AI
Experience: 3+ Years
Location: Remote (Preferred)
Contract Duration: 12+ Months (Long-Term Opportunity)
Work Timings: To be discussed

Key Responsibilities

- Design and implement LLM-powered agents with tool/function calling, dialogue state management, guardrails, and safety mechanisms.
- Build production-grade Retrieval-Augmented Generation (RAG) pipelines.
- Develop indexing, document chunking, embeddings, reranking, and hybrid retrieval solutions for high-precision AI responses.
- Ingest, parse, and process complex PDFs and enterprise documents.
- Implement document intelligence solutions using OCR and multimodal LLMs for text, image, table, and layout understanding.
- Design and continuously improve prompts, prompt templates, system instructions, and few-shot examples.
- Conduct A/B testing and automated evaluations of LLM applications.
- Measure and optimize AI application quality across grounding, hallucination, accuracy, latency, and cost.
- Integrate LLM applications with external tools, APIs, enterprise systems, and data sources.
- Implement integrations using Model Context Protocol (MCP) or similar frameworks.
- Deploy and monitor AI applications in AWS, Azure, or GCP environments.




- Implement appropriate logging, monitoring, and observability for production AI systems.
- Create and maintain project documentation, including requirements, technical designs, architecture documentation, and user guides.

Must-Have Skills & Experience

- 3+ years of experience building ML/AI applications.
- At least 1–2+ years of hands-on experience with LLMs and RAG.
- Strong programming expertise in Python.
- Hands-on experience with:
- LangChain and/or LlamaIndex
- Hugging Face
- LLM APIs and frameworks
- Experience working with vector databases/search platforms, such as:
- Qdrant
- Milvus
- Elasticsearch
- Strong understanding of RAG architecture and retrieval techniques.
- Practical expertise in document chunking strategies.
- Experience selecting, evaluating, and tuning embedding models.
- Experience with reranking and hybrid search/retrieval.
- Experience processing complex documents, including:
- PDF parsing
- OCR
- Table extraction
- Document layout parsing
- Multimodal document understanding
- Experience building LLM agents with tool/function calling.
- Experience integrating tools and enterprise data sources through MCP or similar protocols/frameworks.
- Strong understanding of prompt engineering, few-shot prompting, and prompt optimization.
- Experience deploying AI applications on AWS, Azure, and/or GCP.





Core GenAI Skills

Python | Generative AI | LLM | RAG | Agentic AI | AI Agents | LangChain | LlamaIndex | Hugging Face | Vector Databases | Qdrant | Milvus | Elasticsearch | Embeddings | Chunking | Reranking | Hybrid Search | Prompt Engineering | MCP | Tool Calling | Function Calling | OCR | Multimodal LLMs | Document Intelligence | LLM Evaluation | Guardrails

Nice-to-Have Skills

- Strong understanding of emerging developments across Generative AI, LLMs, and Agentic AI.
- Experience implementing AI guardrails, safety, and responsible AI practices.
- Experience evaluating and improving production LLM applications.
- Experience optimizing LLM applications for accuracy, latency, and cost.
- Experience working in the pharmaceutical industry.

Ideal Candidate

You will be a strong fit if you have actually built and deployed production GenAI applications, rather than only experimenting with LLM APIs.

We are particularly interested in candidates who can demonstrate hands-on experience with RAG pipelines, AI agents, vector databases, document processing/OCR, embeddings, retrieval optimization, and production LLM evaluation.

Apply Now. Interested candidates can share their resume on: [email protected]

If you have 3+ years of AI/ML experience, including hands-on experience with LLMs, RAG, Python, LangChain/LlamaIndex, vector databases, and Agentic AI, we would like to hear from you.

Apply with your updated resume highlighting your LLM/RAG projects, AI agent implementations, document intelligence experience, and production AI deployments.

Pay: ₹50,000.00 - ₹60,000.00 per month

Work Location: Remote

📌 AI Engineer (India)
🏢 Kasmoprav
📍 India