About the Role:

Grade Level (for internal use):

As part of our newly launched AI Center of Excellence (CoE), the AI Engineering Lead will be responsible for building and maintaining the data infrastructure that powers our AI solutions. This hands-on role is ideal for someone with strong experience in data engineering, systems integration, and Agile delivery—who is passionate about enabling innovation through scalable, secure, and high-performing data systems. 
 
You’ll work closely with the AI Strategy Lead, AI Architect Lead, and AI Champions across the business to ensure that AI models are effectively integrated into business workflows and deliver measurable value.

Key Responsibilities 
 

Development & Deployment 

• Lead the hands-on development, deployment, and maintenance of AI solutions using established technology standards. 

• Build and optimize data pipelines to support AI model training, inference, and monitoring. 

• Ensure seamless integration of AI models into existing systems and business processes. 
   

Collaboration & Implementation 

• Partner with cross-functional teams, including business units and IT, to understand data needs and implementation requirements. 

• Work with additional Scrum teams to support Agile delivery of AI initiatives. 

• Translate technical requirements into scalable engineering solutions. 

Monitoring & Optimization 

• Monitor the performance of data pipelines and AI systems to ensure reliability, scalability, and efficiency. 

• Troubleshoot issues and implement improvements to enhance system performance. 

• Maintain documentation and support knowledge sharing across teams. 

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Governance & Compliance 

• Ensure data handling practices meet privacy, security, and compliance standards. 

• Collaborate with data governance and risk teams to uphold responsible AI practices. 

Qualifications 

• Strong experience in data engineering, systems integration, or software development. 

• Proficiency with programming in Python,  data-pipeline tools(e.g., Spark, Airflow), cloud platforms (e.g., GCP, AWS, Azure), and AI frameworks (e.g.,  Google Agent Development Kit, LangChain). 

• Familiarity  with prompt engineering and LLM fundamentals. 

• Experience working in Agile environments and collaborating with Scrum teams. 

• Strong problem-solving skills and attention to detail. 

Preferred Qualifications 

• Exposure to MLOps, CI/CD for data workflows, and model lifecycle management. 

• Familiarity with AI/ML model deployment and monitoring practices. 

• Exposure to Model Context Protocol (MCP),  Multi-tool agent and Multi-agent systems. 

• Experience integrating AI into enterprise systems (e.g., ERP, CRM, or custom platforms). 

• Understanding of data privacy regulations (e.g., GDPR,