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Prompt Engineer

Prompt Engineer

Intellectt IncDelhi, India
7 days ago
Job description

Prompt Engineer

Experience : 3–5 years

Location : Hyderabad (Onsite / Hybrid)

Job Description :

We are looking for a Prompt Engineer with strong software engineering expertise and hands-on experience working with Large Language Models (LLMs) and Agentic AI frameworks. The ideal candidate will design, test, and optimize prompts, retrieval pipelines, and agentic workflows that power intelligent, production-grade AI systems.

Key Responsibilities :

  • Design, prototype, and refine prompts for LLMs (OpenAI, Anthropic, Gemini, Llama, etc.).
  • Build and integrate LLM-based services via APIs with FastAPI (routers, DI, auth, rate limiting).
  • Implement Retrieval-Augmented Generation (RAG) workflows — document parsing, chunking, embeddings, vector search, and hybrid retrieval.
  • Develop agentic flows and state machines using LangGraph; build chains / tools using LangChain.
  • Create and maintain testing frameworks for prompts, retrieval logic, and chain / tool performance (A / B testing, relevance, latency, and cost).
  • Manage vector database integrations (FAISS, Pinecone) and ensure retrieval accuracy.
  • Collaborate on end-to-end API development, CI / CD integration, and system monitoring.
  • Maintain documentation, best practices, and advocate for prompt engineering standards across teams.

Must-Have Skills :

  • 3–5 years of software engineering experience with strong Python skills.
  • Proven hands-on experience with FastAPI, LLMs (OpenAI, Anthropic, Gemini, Llama), and function / tool calling.
  • Practical experience implementing RAG, embeddings, hybrid retrieval, and document chunking.
  • Proficiency with LangGraph and / or LangChain for agentic and chained workflows.
  • Experience with vector databases (FAISS, Pinecone, Weaviate) and document preprocessing.
  • Familiarity with Git, Docker, and CI / CD pipelines.
  • Strong communication and collaboration skills.
  • Nice-to-Have Skills :

  • Experience in LLM fine-tuning (LoRA, quantization) and monitoring prompt performance.
  • Knowledge of cloud deployment (AWS / Azure / GCP) and LLM observability (latency, cost tracking).
  • Prior exposure to regulated domains such as healthcare or life sciences.
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    Engineer • Delhi, India

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