Prompt Engineers

Axsyntra; Bengaluru; On-site; INR 600,000 - 900,000; Full time

Job summary

A leading AI solutions provider is seeking a Prompt Engineer to design, test, and optimize prompts for large language models. You will work with AI development and product teams to translate business objectives into effective prompts, ensuring high-quality outputs. The ideal candidate has strong English communication skills and familiarity with LLMs such as GPT and Claude. This position offers an opportunity to significantly impact AI outcomes and improve collaboration across teams in Indore District, Madhya Pradesh.

Qualifications

• Strong command of English for precise communication.
• Familiarity with LLMs like GPT, Claude, Gemini, or LLaMA.
• Understanding of prompt tuning and few-shot learning.

Responsibilities

• Create, test, and refine prompts for various AI use cases.
• Study LLM behavior and improve model performance.
• Collaborate with product managers and developers.

Skills

Strong command of English

Familiarity with LLMs

Understanding of prompt tuning

Experience in Python or scripting languages

Tools

Python

JSON

Job description

We are looking for a Prompt Engineer to design, test, and optimize prompts that unlock the full potential of large language models (LLMs). You will work closely with our AI development, data science, and product teams to translate business objectives into precise, efficient, and context-aware prompts. Your role will bridge the gap between human intent and AI output, ensuring accuracy, creativity, and consistency.

Required Skills & Experience

• Strong command of English (and/or other languages) for precise, context-aware communication.
• Familiarity with LLMs like GPT, Claude, Gemini, or LLaMA.
• Understanding of prompt tuning, few-shot learning, and chain-of-thought prompting.
• Experience in Python, JSON, or scripting languages for automation is a plus.

Key Responsibilities

• Prompt Design & Optimization – Create, test, and refine prompts for different AI use cases, ensuring high-quality outputs.
• LLM Behavior Analysis – Study how models respond to various prompts, identifying patterns and improving performance.
• Cross‑Team Collaboration – Work with product managers, developers, and domain experts to align AI outputs with project goals.

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