Prompt Engineer

Job Description

The Prompt Engineer designs, tests, and optimizes natural language prompts for large language models (LLMs) to produce reliable, high-quality outputs for client use cases. This role combines experimentation, data analysis, and documentation to create reusable prompt frameworks that enhance performance, reduce costs, and scale across projects.

Key Responsibilities

Design and iterate prompts to meet target outcomes across various LLMs.

Develop and maintain prompt libraries with version control for reusability.

Conduct A / B testing to measure prompt quality, consistency, and token efficiency.

Document prompt patterns, edge cases, and troubleshooting guidelines.

Work with AI Solutions Architects to integrate prompts into client workflows.

Collaborate with Customer Success to gather client feedback and refine prompts.

Monitor model updates and adapt prompts to ensure continued performance.

Core Technical Skills

Understanding of AI and LLMs : Familiarity with how models like GPT work, including natural language processing (NLP), machine learning fundamentals, and limitations of generative AI.

Prompting Techniques : Expertise in methods such as chain-of-thought, few-shot prompting, role-playing, and structured outputs (e.g., JSON).

Python Programming : Experience in using Python for scripting, API integration, testing prompts, and automation.

Data Handling : Proficiency in data preprocessing, evaluation metrics, and fine-tuning models for specific tasks.

API & Integration Knowledge : Experience with REST / GraphQL APIs, and workflow automation tools (e.g., Zapier, Make).

Version Control & Collaboration Tools : Familiarity with Git / GitHub, Jira, and Confluence for versioning and team collaboration.

Soft and Creative Skills

Strong Communication : Excellent written communication skills, with clarity in instructions and an understanding of user needs.

Creativity & Problem-Solving : Ability to think iteratively, refine prompts, experiment with phrasing, and address ambiguous requirements.

Patience & Adaptability : Comfortable adapting approaches based on new insights and client feedback.

Collaboration : Ability to work effectively with cross-functional teams, including clients, product managers, and developers, to integrate AI solutions.

Success Metrics

Prompt success rate (accuracy, relevance, user satisfaction).

Reduction in token usage and cost per output.

Time-to-deliver optimized prompts.

Contribution to the prompt knowledge base.

Requirements

1–3+ years of experience working with AI, machine learning, NLP, or applied LLM solutions (including project or academic experience)

Strong understanding of LLMs, NLP fundamentals, and generative AI limitations

Hands-on experience designing, testing, and optimizing prompts across multiple LLMs

Expertise in prompting techniques (few-shot, chain-of-thought, role-based, structured outputs)

Proficiency in Python for scripting, prompt testing, automation, and API integration

Experience with prompt evaluation, A / B testing, and token / cost optimization

Familiarity with APIs, version control (Git), and collaboration tools

Strong written communication and documentation skills

Creative, analytical problem-solver comfortable with experimentation and ambiguity

Ability to collaborate cross-functionally and adapt to evolving models and client needs

Benefits

Paid Leaves & Birthday Off : Take time when you need it, and convert unused leave into cash! Plus, enjoy an extra day off on your birthday.

Comprehensive Health Insurance : Coverage starts from day one and extends to one dependent.

Performance-Based Salary Increase : Enjoy a raise after regularization

Annual Salary Adjustments : We recognize long-term commitment with yearly salary increases.

Employee Recognition : Be rewarded for your hard work with incentives and recognition.

Engaging Team Activities : Join in on Family Days, Summer Splash, and other fun events that strengthen the iReply community.aptos

Requirements

1–3+ years of experience working with AI, machine learning, NLP, or applied LLM solutions (including project or academic experience) Strong understanding of LLMs, NLP fundamentals, and generative AI limitations Hands-on experience designing, testing, and optimizing prompts across multiple LLMs Expertise in prompting techniques (few-shot, chain-of-thought, role-based, structured outputs) Proficiency in Python for scripting, prompt testing, automation, and API integration Experience with prompt evaluation, A / B testing, and token / cost optimization Familiarity with APIs, version control (Git), and collaboration tools Strong written communication and documentation skills Creative, analytical problem-solver comfortable with experimentation and ambiguity Ability to collaborate cross-functionally and adapt to evolving models and client needs