1. Business Requirement Analysis & AI Use Case Definition: 

Activities involving understanding business needs and translating them into AI‑enabled solutions: 

• Work closely with stakeholders (Engineering, Estimating, Operations, Management) to identify high-impact use cases suitable for AI adoption.  
• Analyze current workflows and pain points to define clear functional and technical requirements.  
• Propose AI solutions aligned with business value, feasibility, and data availability.  
• Prioritize initiatives based on ROI, scalability, and operational impact. 

 

2. AI Solution Design & Development: 

• Design, develop, and deploy custom AI agents using Microsoft Copilot Studio, Microsoft 365 Copilot, and Azure AI services to support real business workflows. 
• Build and maintain AI‑powered tools integrated with Microsoft 365 applications, including Teams, Outlook, SharePoint, Excel, Word, and the Power Platform, to improve productivity and information flow. 
• Implement and optimize prompt engineering, conversation design, and orchestration logic to ensure accurate, reliable, and business‑ready AI outputs. 
• Design scalable conversation flows and agent behaviors aligned with business rules, data context, and user experience. 
• Validate AI agent performance with end users and continuously refine prompts, logic, and integrations based on feedback and observed outcomes. 

 

3. User Enablement & Collaboration: 

• Act as a trusted advisor to business teams on how AI can support their daily work. 
• Train users on adopted AI tools, including proper usage and interpretation of outputs. 
• Gather user feedback and continuously refine tools to better meet operational needs. 
• Collaborate with engineering, IT, and management teams to ensure alignment with company strategy. 

 

4. Quality, Governance & Tooling: 

• Ensure AI solutions follow company standards for quality, security, and documentation. 
• Maintain clear documentation for AI tools, workflows, prompts, and data dependencies. 
• •upport governance practices to ensure responsible and ethical use of AI within the organization. 

 

5. Continuous Improvement & Innovation: 

Activities improving processes, tools, and ways of working: 

• Proactively research emerging AI technologies and identify practical applications relevant to the business. 
• Drive continuous improvement initiatives by proposing enhancements to existing AI tools and workflows. 
• Share lessons learned, best practices, and success stories across the organization. 
• Support management in shaping the long‑term AI roadmap for the company.v

Required: 

• Bachelor’s degree in Engineering, Computer Science, Data Science, Information Systems, or related fields. 
• Fluent English (minimum TOEIC score 700 or equivalent). 
• 3+ years of experience applying AI, automation, or data‑driven solutions to real‑world business problems. 
• Strong understanding of applied AI concepts, including: 

• • Large Language Models (LLMs) 
  • Prompt engineering 
  • Information extraction and document processing 
  • Automation and workflow integration 
• Ability to translate business needs into practical, usable technical solutions. 
• Strong analytical and problem‑solving skills. 
• Clear communication skills to explain technical concepts to non‑technical stakeholders. 

 

Preferred: 

• Familiarity with tools such as: 

• • Python / scripting for automation 
  • AI APIs or platforms (e.g., LLM frameworks, OCR, vision models) 
  • Low‑code / no‑code automation platforms 
• Experience working with global teams and diverse business stakeholders. 
• Strong curiosity, hands‑on mindset, and willingness to experiment and iterate. 
• Hands‑on experience with Microsoft Copilot Studio, Power Platform (Power Automate, Power Apps), and Azure AI services. 
• Experience designing enterprise‑grade conversational AI or AI agents with strong focus on quality, governance, and user adoption is an advantage.