Artificial Intelligence Engineer with Pharama(MUST)

Role: AI Engineer (Must have Exp in Pharma industry) ---Don't APPLY Healthcare Location: PAN India (Remote) Timings -- 1:30 PM IST to 10:30 PM IST Key Responsibilities Conversational Agents : Implement LLM agents with tool/function calling, dialogue state, guardrails, and safety. RAG Pipelines : Build indexing, chunking , embeddings , reranking, and hybrid retrieval for high-precision answers. Document AI : Ingest and parse complex PDFs using OCR and multimodal LLM image understanding (sending full images to an LLM to describe, detect structure, and extract context) plus table extraction and layout-aware parsing. Prompt Engineering : Design and iterate prompts, templates, few-shot examples; run A/B and automated evaluations. Evaluation & Operations : Measure grounding, hallucination, latency, and cost; deploy and monitor in cloud with observability. Project documentation and communication : Creating and maintaining the written project documentations including requirements, technical designs, test plans, runbooks, release notes, user guides, risk/issue logs, and change records, as well as status updates, meeting notes, incident/outage notices, decision summaries, Skills Essential Demonstrated business analysis skills with 3+ years of experience leading customer/client facing workshops and discussions. 3+ years building ML/AI applications, including 12+ years with LLMs + RAG . Strong Python ; experience with LangChain/LlamaIndex , Hugging Face. Hands-on with vector databases (Qdrant/Milvus/ElasticSearch), semantic search, and rerankers. Practical expertise in chunking strategies (semantic, layout-aware) and embedding selection/tuning. Experience processing complex documents: table extraction, layout parsing, OCR , and multimodal LLM-based image description/structure detection . Experience integrating tools and data sources via protocols like MCP (or similar agent-tool frameworks). Solid prompt engineering and cloud deployment (AWS/Azure/GCP), containers, and CI/CD. Desirable Sound understanding of emerging developments in AI, including generative AI and agentic AI, to support the framing of innovative aspirations and solutions. Experience in the pharmaceutical industry. Role: AI Engineer (Must have Exp in Pharma industry) ---Don't APPLY Healthcare Location: PAN India (Remote) Timings -- 1:30 PM IST to 10:30 PM IST Key Responsibilities Conversational Agents : Implement LLM agents with tool/function calling, dialogue state, guardrails, and safety. RAG Pipelines : Build indexing, chunking , embeddings , reranking, and hybrid retrieval for high-precision answers. Document AI : Ingest and parse complex PDFs using OCR and multimodal LLM image understanding (sending full images to an LLM to describe, detect structure, and extract context) plus table extraction and layout-aware parsing. Prompt Engineering : Design and iterate prompts, templates, few-shot examples; run A/B and automated evaluations. Evaluation & Operations : Measure grounding, hallucination, latency, and cost; deploy and monitor in cloud with observability. Project documentation and communication : Creating and maintaining the written project documentations including requirements, technical designs, test plans, runbooks, release notes, user guides, risk/issue logs, and change records, as well as status updates, meeting notes, incident/outage notices, decision summaries, Skills Essential Demonstrated business analysis skills with 3+ years of experience leading customer/client facing workshops and discussions. 3+ years building ML/AI applications, including 12+ years with LLMs + RAG . Strong Python ; experience with LangChain/LlamaIndex , Hugging Face. Hands-on with vector databases (Qdrant/Milvus/ElasticSearch), semantic search, and rerankers. Practical expertise in chunking strategies (semantic, layout-aware) and embedding selection/tuning. Experience processing complex documents: table extraction, layout parsing, OCR , and multimodal LLM-based image description/structure detection . Experience integrating tools and data sources via protocols like MCP (or similar agent-tool frameworks). Solid prompt engineering and cloud deployment (AWS/Azure/GCP), containers, and CI/CD. Desirable Sound understanding of emerging developments in AI, including generative AI and agentic AI, to support the framing of innovative aspirations and solutions. Experience in the pharmaceutical industry.