PureCode AI - LLM & Prompt Engineer (2-6 yrs)

LLM & Prompt Engineer

About PureCode AI :

PureCode is a front-end developer tool where engineers can use text to describe and generate or customize software user interfaces - (and soon entire projects). Our goal is tobuild a must use developer tool for front-end engineers to build web software 100x faster! We are headquartered in Austin, TX, USA with engineering offices in Bangalore, India. This position is for exclusively in office work in Bangalore.

Please visit our site to understand our product before applying https://purecode.ai/

Responsibilities :

- Develop and optimize prompts for AI systems to assist developers in generating high-quality code, improving documentation, and automating tasks.

- Designing, Developing and Refining prompts to enhance the quality and relevance of generated response.

- Monitor and analyze prompt's performance to identify areas of improvements.

- Understand user behavior and requirements and develop accordingly.

- Stay proactive in identifying opportunities for innovation and improvement in our AI systems.

- Stay up to date with advancements in AI, NLP, and prompt engineering, and apply this knowledge to improve our products and processes.

- Conduct experiments to test and evaluate the effectiveness of different prompts in producing optimal results for end users.

Qualifications :

- Knowledge of LLM parameters and configuring these parameters to get different results for prompt.

- Understanding of all prompt elements and experience in modifying those elements to get better results.

- Experience with existing prompting techniques.

- Experience with using suitable prompts for various applications (e.g. Generating code, Generating data, etc.).

- Experience with RAG and handling hierarchical data (e.g. Codebase) for RAG.

- Knowledge of capabilities of various LLMs and how can we use different prompts efficiently to improve the capacity of LLMs.

- Knowledge of scaling, agents, efficiency, hallucination, prompt injection, etc.

- Understanding of Graph databases and Tabular databases and utilization of prompts to make LLM interact with these databases.

- Knowledge of latest research on prompt engineering for LLMs.