Ai Engineer

Programming & Software Engineering: Expertise in Python (and optionally Java, JavaScript, or C#), unit testing, and version control (Git).

AI/ML Knowledge: Solid grasp of machine learning and AI concepts, model behavior, and experience with NLP or chatbots.

Prompt Engineering: Experience crafting and iterating prompts, including few-shot examples and output formatting techniques.

RAG and Data Handling: Familiarity with embedding models, vector databases, and unstructured data processing.

API and Integration Skills: Building and consuming RESTful APIs, microservices, and handling JSON/XML data formats.

Data Structures & Algorithms: Knowledge of lists, dictionaries, trees/graphs, and their application in efficient agent design.

Debugging & Problem-Solving: Strong troubleshooting abilities to distinguish between model and code issues.

Agile and Collaborative Mindset: Comfortable working in sprints, collaborating across teams, and communicating technical needs.

Domain Adaptability: Ability to quickly learn new industry concepts for tailored agent solutions.

Attention to Detail & Quality: Consideration of edge cases, proper data handling, and thorough testing.

Ethical Awareness: Recognize bias, confidentiality issues, and flag questionable requests.