We are looking for an innovative and experienced Senior AI Engineer to join our Global Customer AI Solutions team. Reporting to the Senior Director, you will play a critical role in designing, developing, and deploying AI solutions that propel innovation and optimize our global operations. You will collaborate with cross-functional teams to build robust, scalable AI systems, ensuring successful integration and delivery across multiple business segments.

REQUIRED QUALIFICATIONS:

• Professional Experience: At least 5 years of experience in AI engineering with a proven track record of successfully building and deploying AI solutions.
• Technical Proficiency: Expertise in AI frameworks and libraries such as LangChain, LangGraph, or OpenAI SDK, and programming languages like Python, Java, or R.
• Educational Background: Bachelor’s degree in computer science, Engineering, or a related field; equivalent technical experience is also considered.

PREFERRED QUALIFICATIONS:

• Prompt Engineering: Strong skills in prompt engineering and indexing/retrieval techniques.
• Distributed Systems: Experience with distributed computing frameworks and cloud platforms like AWS, Azure, or Google Cloud.
• Machine Learning Expertise: Strong knowledge of machine learning algorithms and experience in applying pre-built models.
• Data Engineering Skills: Solid understanding of data engineering principles, including data pipelines and ETL processes.
• Problem-Solving Ability: Exceptional problem-solving skills with the capacity to tackle complex technical challenges.
• Effective Communication: Excellent communication skills to effectively collaborate with cross-functional teams and convey technical concepts to non-technical stakeholders.

• AI Solution Implementation: Leverage and integrate advanced AI models, such as large language models (LLMs), to solve complex business problems and enhance operational efficiency.
• Seamless Integration: Partner with data scientists, engineers, and business stakeholders to gather requirements and integrate AI solutions smoothly with existing systems.
• Technical Mentorship: Lead and mentor junior engineers, fostering a culture of innovation and collaboration within the team.
• Scalable Infrastructure: Develop and maintain scalable AI platforms and infrastructure to facilitate the deployment and management of AI models in production.
• Data Pipeline Management: Work with data engineers to establish high-quality data pipelines that ensure efficient data processing for AI applications.
• Model Optimization: Regularly assess and enhance AI models and systems for optimal performance, accuracy, and reliability.
• Responsible AI Practices: Advocate for and apply responsible AI practices and rigorous testing methodologies.
• Continuous Innovation: Keep up with the latest AI technologies and research, incorporating new methodologies to enhance our solutions.
• Efficient Human Feedback Loops : Implement efficient human feedback loops to refine and improve AI actioning solutions.