Prompt Engineer

Job Summary:

We are looking for an experienced Prompt Engineer to work closely with our content creators, product teams, and data scientists to design, develop, and refine high-performing prompts, with a strong focus on optimizing prompt usage for GitHub Copilot. You will be instrumental in enabling more efficient AI-assisted coding workflows and enhancing overall developer productivity.

Key Responsibilities:

Prompt Development & Optimization:

. Rapidly design, develop, and iterate prompts to achieve coding goals such as generating code snippets, debugging, and unit test generation.

. Refine prompts for improved performance and relevance across different programming languages and frameworks.

Context & Constraint Management:

. Incorporate contextual information (codebase, language, libraries) and apply constraints (e.g., style guides, performance) to fine-tune prompt responses.

Prompt Testing & Evaluation:

. Conduct A/B testing and controlled experiments to evaluate prompt effectiveness.

. Analyze output from Copilot and other LLMs to identify opportunities for improvement.

Prompt Library & Documentation:

. Create and maintain a centralized repository of effective prompts for reuse across teams.

. Develop internal documentation, best practices, and knowledge bases for future prompt engineering efforts.

Developer Enablement:

. Build tutorials, guides, and educational resources to enhance prompt engineering skills across development teams.

. Offer training sessions and workshops to onboard teams into prompt engineering methodologies.

Research & Innovation:

. Stay up to date with the latest trends in NLP, LLMs, and AI-driven development tools.

. Experiment with new prompting strategies, fine-tuning methods, and chaining techniques.

Qualifications:

. 8 years of experience in software development, machine learning, or AI-focused engineering roles.

. Proven experience with GitHub Copilot, OpenAI APIs, or similar LLM platforms.

. Strong background in natural language processing (NLP), prompt engineering, and AI-assisted software development.

. Proficiency in one or more programming languages (Python, JavaScript, Java, etc.).

. Solid understanding of machine learning workflows, model tuning, and evaluation techniques.

. Excellent problem-solving, experimentation, and analytical skills.