Department: AI / Technology / Product Development
Experience: 1–3 Years
Qualification: B.E./B.Tech/MCA/BCA / Degree in Computer Science, AI/ML, Data Science, or related field
Job Summary
We are looking for a creative and analytical Prompt Engineer to design, test, optimize, and implement prompts for AI and Large Language Model (LLM) applications. The candidate will work with AI models to improve response quality, accuracy, consistency, and usefulness for various business applications.
Key Responsibilities
Design and develop effective prompts for LLMs and Generative AI applications.
Create, test, and optimize prompts for different business use cases.
Experiment with prompt structures, instructions, context, examples, and output formats.
Evaluate AI-generated responses for accuracy, relevance, consistency, and quality.
Develop prompt templates and reusable prompt libraries.
Work with AI/ML and software development teams to integrate prompts into applications and workflows.
Perform testing and benchmarking of different prompts and AI models.
Identify model limitations, hallucinations, inconsistencies, and potential biases.
Develop techniques such as few-shot prompting, chain-of-thought alternatives, role-based prompting, structured prompting, and context engineering where appropriate.
Work with APIs and AI platforms to integrate LLM capabilities into products.
Maintain documentation of prompts, experiments, test results, and optimization methods.
Analyze user feedback and continuously improve AI outputs.
Stay updated with developments in Generative AI, LLMs, AI agents, and prompt engineering techniques.
Support responsible and secure use of AI in business applications.
Key Skills & Technical Requirements
Strong understanding of Generative AI
LLMs
NLP
and AI concepts. Practical experience with AI tools and LLM platforms such as OpenAI
Google Gemini
Anthropic Claude
or similar platforms. Strong written communication and instruction-design skills. Knowledge of Python and APIs is preferred. Understanding of JSON
structured outputs
and data formats. Familiarity with model evaluation
testing
and benchmarking. Knowledge of RAG
embeddings
vector databases
and AI agents will be an advantage. Basic understanding of software development and Git is preferred.
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