Prompt Engineer

Prompt Engineer Hyderabad Hybrid Exp- 2+ yrs About the Role We are looking for a talented and detail-oriented Prompt Engineer to join our growing AI team. In this role, you will be responsible for crafting, evaluating, and optimizing prompts that drive the behavior of LLM-powered applications and intelligent agent systems. You will play a pivotal role in bridging the gap between business requirements and AI-driven outcomes, ensuring that our systems perform accurately, safely, and reliably in production. Key Responsibilities ● Design, test, and systematically optimize prompts for LLM-powered applications and AI agent pipelines. ● Create and continuously refine system prompts, guardrails, evaluation prompts, and multi-agent interaction frameworks. ● Collaborate closely with AI backend engineers to seamlessly integrate prompts into production APIs and agent workflows. ● Develop comprehensive prompt evaluation datasets, scoring methodologies, and automated testing pipelines to ensure consistent quality. ● Experiment with Retrieval-Augmented Generation (RAG) pipelines, memory systems, tool-calling mechanisms, and agent orchestration strategies. ● Analyze agent failures and iterate on prompt designs using structured evaluation frameworks and real-world production feedback. ● Partner with product and business stakeholders to translate functional requirements into precise, well-defined AI behaviors. ● Document prompting strategies, established best practices, and maintain a library of reusable prompt templates for organizational use. Skills & Memory Required Qualifications ● 2+ years of hands-on experience working with Large Language Models (LLMs) and Generative AI in production environments. ● Strong command of prompt engineering techniques, including reasoning, information extraction, summarization, and agentic workflow design. ● Proven experience with synthetic dataset generation and AI evaluation methodologies. ● Familiarity with Model Context Protocols (MCP), AI gateways, and model routing strategies. ● Solid understanding of AI safety principles, prompt injection risks, and secure agent design practices. ● Experience working with AI frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent. ● Demonstrated experience in building and evaluating AI agents utilizing tool-calling, RAG architectures, and memory systems. ● Strong understanding of hallucination mitigation strategies and their practical application in production systems. ● Experience with structured output generation and JSON schema design for LLM responses. ● Proven ability to design and implement evaluation pipelines assessing LLM quality, accuracy, latency, and safety. ● Comfortable working with Python and LangChain, with a strong ability to collaborate effectively with AI engineers. ● Hands-on experience with AI monitoring and evaluation tools such as LangSmith, DeepEval, Ragas, or similar platforms. ● Clear understanding of the distinctions between local and cloud-based LLM inferencing, and the implications of each in production contexts. Interested candidates can share their updated CV at seema.bisht@glovetalent.com