Artificial Intelligence (AI) Engineer I
CYNET SYSTEMS INC.
Wilmington, United States of America
11 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
JuniorJob location
Wilmington, United States of America
Tech stack
API
Agile Methodologies
Artificial Intelligence
Data analysis
Python
Machine Learning
Microsoft Power Automate
Large Language Models
Prompt Engineering
Zapier
AI Platforms
Information Technology
Extreme Programming (XP)
Job description
- Partner with product managers and developers to support AI solution delivery across the product lifecycle.
- Help define, document, and communicate clear business and technical requirements.
- Support the implementation of AI use cases using approved enterprise AI tools.
- Contribute to the coordinated execution of AI initiatives across engineering teams.
- Create, test, and refine prompts for generative AI applications.
- Participate in prompt tuning and experimentation to improve model outputs.
- Assist with integrating AI services and models into applications and workflows using APIs.
- Build small prototypes, scripts, or workflow automations using Python.
- Explain technical concepts in a clear, practical way for non technical stakeholders.
- Support training, demos, and coaching to help teams adopt AI tools effectively.
- Identify opportunities where AI can streamline work, reduce effort, or improve outcomes.
Requirements
Requirement/Must Have:
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- At least 1 year of experience in data science, analytics, automation, or AI related work., * Basic understanding of AI/ML concepts, including large language models and prompt engineering.
- Foundational ability to read and write Python for prototypes, automation, or simple integrations.
- Understanding of APIs and how to connect scripts or tools to external services.
- Strong communication skills, especially when explaining technical topics to non technical audiences.
- Exposure to workflow automation tools (Power Automate, Logic Apps, Zapier).
- Exposure to RAG concepts or vector databases.
- Awareness of Agile, Lean, or XP delivery methodologies.
- Ability to identify high value AI use cases and support ideation and scoping.
- Coursework, internships, or hands on experience in data science, analytics, automation, or AI.