Generative AI Engineer

Job Description:             

• Proven experience leading and managing AI initiatives within an organization.
• Strong understanding of generative AI technologies, their capabilities, and potential applications.
• Excellent communication and interpersonal skills to build strong relationships with stakeholders across various departments.
• Strategic thinking and problem-solving skills to identify opportunities and develop solutions.
• Passion for innovation and a commitment to staying updated on the latest advancements in generative AI.
• At least 4 years of hands-on experience in AI and machine learning, with last 2 years on Generative AI.
• Proficiency in: AI and ML frameworks, Azure AI Stack, RAG, Semantic Kernal, LangChain, Python, React, REST API’s Solid understanding of Azure OpenAI and other leading GenAI models from Anthropic, Meta, Google & Amazon.
• Experience in designing and implementing enterprise search frameworks.
• Excellent analytical skills, with the ability to use data to inform product decisions and drive continuous improvement.
• Strong cross-functional collaboration skills, with the ability to work effectively with engineering, design, data science, and business development teams.
• Excellent communication skills, with the ability to clearly articulate complex product concepts to both technical and non-technical stakeholders.
• Proven ability of delivering in a fast-paced environment involving multiple stakeholders
• Strong commitment to professional client service excellence
• Ability to coach junior staff.

Competencies:  Design for GenAI

Essential Skills: 

• GenAI Specialist-Technical Leadership and Strategy: Establish the technical vision and architecture for generative AI projects.
• Develop a comprehensive roadmap for integrating generative AI technologies throughout the organization.
• Identify high-impact opportunities for generative AI across various departments and functions.
• Innovation and Prototyping: Lead the ideation and prototyping of new generative AI applications, exploring novel use cases, and pushing the boundaries of what’s possible with AI.
• Facilitate the transition of prototypes into scalable, production-ready solutions.