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We are seeking a contractor to help deliver AI solutions that improve productivity and engineering efficiency across the business. In this role, you will work with product managers, developers, and business stakeholders to support AI use cases from concept through deployment and adoption. You will help define requirements, contribute to lightweight prototypes, support integrations, and ensure solutions meet stakeholder needs. You will also help teams understand and adopt AI tools by translating technical concepts into practical guidance.
Job Responsibility
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
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.
Nice to have
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