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Responsibilities

• Design, develop, and maintain prompt frameworks for LLM applications.
• Build and manage automated evaluation frameworks to measure model performance.
• Conduct A/B testing across prompt variations and model versions.
• Convert product requirements into effective prompt instructions and guardrails.
• Partner with ML engineers and product teams to determine AI architecture needs.
• Create and maintain a centralized prompt repository with version control.
• Lead red-teaming and adversarial testing exercises for LLMs.
• Define evaluation criteria and quality standards for AI-generated outputs.
• Mentor engineers and stakeholders on prompt engineering best practices.
• Present prompt strategies and benchmark results to teams.
• Apply advanced prompting techniques like chain-of-thought and zero-shot.
• Drive prompt testing, evaluation, benchmarking, and optimization.
• Improve AI response quality through systematic assessment and tuning.
• Manage context handling and prompt orchestration for AI workflows.

Requirements

• Strong programming and scripting skills in C#, Python, or Javascript.
• Experience building automation, evaluation pipelines, APIs, or AI-powered applications.
• Hands-on experience with LLM platforms, prompt engineering, and AI application development.
• Familiarity with prompt orchestration frameworks, vector databases, RAG architectures, and AI agent workflows.
• Understanding of data analysis, experimentation, benchmarking, and performance optimization.
• Experience with version control systems, CI/CD pipelines, and cloud platforms.
• Strong knowledge of REST APIs, JSON, and system integration patterns.
• Ability to collaborate effectively with cross-functional teams to deliver AI solutions.

Skills

• C#
• Python
• Javascript
• LLM platforms
• Prompt engineering
• Model evaluation
• AI application development
• Prompt orchestration frameworks
• Vector databases
• RAG architectures
• AI agent workflows
• Data analysis
• Experimentation
• Benchmarking
• Performance optimization
• Version control systems
• CI/CD pipelines
• Cloud platforms
• REST APIs
• JSON
• System integration patterns

Experience Level

• 4-7 years of combined experience in NLP, AI/ML products, software development, technical writing, or related fields.
• At least 2 years of direct, hands-on prompt engineering experience with production LLM applications.
• Proven track record of owning and managing prompt systems end-to-end in production.