GEN AI/Prompt engineer

Role Overview

We are seeking a highly skilled and innovative GenAI Engineer / Prompt Engineer with 3–6 years of experience in building AI-powered applications leveraging Large Language Models (LLMs), Generative AI frameworks, and prompt engineering techniques. The ideal candidate should have hands-on experience in designing AI agents, optimizing prompts, integrating LLM APIs, and developing scalable AI solutions for enterprise use cases.

Responsibilities

• Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs).
• Create, test, and optimize prompts for accuracy, consistency, and performance.
• Build AI agents and multi-agent workflows for enterprise applications.
• Integrate LLM APIs such as OpenAI, Anthropic Claude, Gemini, or open-source models.
• Develop Retrieval-Augmented Generation (RAG) and Agentic AI solutions.
• Work on vector databases, embeddings, semantic search, and knowledge retrieval systems.
• Collaborate with data engineers and application teams for end-to-end AI solution integration.
• Evaluate model performance and improve outputs through prompt tuning and experimentation.
• Implement guardrails, security, and responsible AI practices.
• Build reusable AI workflows, templates, and accelerators.
• Stay updated with emerging trends in GenAI, LLMs, and AI frameworks.

Requirements

• Strong understanding of Large Language Models (LLMs), Prompt Engineering, RAG, and AI Agents.
• Hands-on experience with Python, REST APIs, and JSON handling.
• Experience with LangChain, LangGraph, LangSmith, LlamaIndex, or Semantic Kernel.
• Exposure to cloud platforms like Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Experience with Vector databases (Pinecone, ChromaDB, FAISS, Weaviate).
• Knowledge of Git, CI/CD, and Docker.

Skills

• Python
• LangChain
• LLMs
• RAG
• Vector Databases

Nice to Have

• Bachelor’s or Master’s degree in Computer Science, AI, or Data Science.
• Experience building enterprise AI copilots or conversational AI applications.
• Exposure to multi-modal AI solutions (text, image, audio).
• Experience working with healthcare, supply chain, or financial domains.