Generative AI Prompt Engineer

Key Responsibilities:

• Design, implement, and optimize complex prompts for large language models (LLMs) like GPT to achieve domain-specific accuracy and efficiency.
• Create custom tools for creating knowledge bases for AI assistants, enabling scalable and efficient integration of domain-specific knowledge for improved performance.
• Apply machine learning (ML) and natural language processing (NLP) algorithms to refine prompt structures and improve performance across multiple languages and contexts.
• Collect and analyze prompt-response metrics using statistical and ML tools to identify and resolve gaps, biases, or inefficiencies.
• Use A/B testing and reinforcement learning techniques to evaluate and enhance prompt effectiveness in dynamic environments.
• Fine-tune and optimize existing language models using transfer learning and other advanced ML techniques to improve domain adaptability and precision.
• Collaborate with data scientists to preprocess datasets, ensuring model readiness and compliance with domain-specific constraints.
• Partner with software engineers, data engineers, and UX designers to integrate prompt systems into broader applications and pipelines.
• Develop reusable APIs and libraries for prompt testing, evaluation, and scalability across teams.
• Monitor and mitigate biases in model outputs by implementing fairness, inclusivity, and ethical AI standards.
• Document complex prompt engineering workflows and frameworks for reproducibility and scalability.
• Conduct workshops and training sessions to upskill team members in prompt optimization and best practices.
• Stay updated with the latest advancements in AI research and incorporate cutting-edge techniques into production systems.

Required Qualifications:

Education:

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

Experience:

• 4+ years of experience in software engineering, data science, or AI development with a focus on development of scalable systems, APIs, or AI-driven applications.
• Experience with LLMs and Gen AI platforms like OpenAI, Anthropic, Google AI, Llama, and Perplexity.
• Must have hands-on experience with prompt engineering, including designing, testing, and optimizing prompts for LLMs.
• Experience in Prompt Engineering techniques like iterative prompt refinement, dynamic prompt construction, and chaining prompts for complex workflows.
• Proficiency with tools such as OpenAI Playground, Hugging Face, LangChain, and API integrations for testing, debugging, and managing prompt performance is essential.
• Knowledge of reinforcement learning, meta-learning, or unsupervised learning techniques.
• Experience with LLMs and integrating them into production systems.
• Experience with data analysis, NLP for AI model optimization.

• Experience in programming languages Python, R, Java, or Scala, JavaScript, with experience in building and deploying APIs and frameworks such as LangChain, TensorFlow, PyTorch.
• Proficiency in data manipulation libraries like NumPy and Pandas.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Understanding of ML algorithms, optimization techniques, and model evaluation methods.
• Working knowledge of statistical analysis, A/B testing, and handling large datasets.
• Research ability: you have proven track record in conducting and analyzing both qualitative and quantitative research

Soft Skills:

• Exceptional problem-solving and analytical abilities.
• Strong collaboration and communication skills to work effectively with cross-functional teams.
• Passion for emerging AI trends and the ability to anticipate their impact on business and technology.