Lead GenAI

Key Responsibilities:

Lead AI Strategy: Define and execute the AI strategy, focusing on the integration of generative AI with knowledge graphs to create autonomous agents that enhance business operations.
Develop Autonomous Agents: Design and implement agentic AI systems that operate independently, make decisions, and interact with users and other systems without direct human intervention.
Integrate Knowledge Graphs: Utilize knowledge graphs to provide structured, contextual information that enhances the reasoning capabilities of AI agents, ensuring accurate and relevant outputs.
Collaborate Across Teams: Work closely with data scientists, engineers, product managers, and business stakeholders to align AI initiatives with organizational goals and ensure seamless integration of AI solutions.
Ensure Ethical AI Practices: Establish frameworks for responsible AI development, focusing on transparency, accountability, and fairness in autonomous AI systems.
Drive Innovation: Stay abreast of the latest advancements in AI, machine learning, and knowledge representation to continuously enhance the capabilities of AI agents.
 

Qualifications:

Educational Background: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. A Ph.D. is a plus.
Experience: 14+ years in AI/ML development, with at least 4 years in a leadership role focused on generative AI and knowledge graphs.
Technical Expertise:
Proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, or similar.
Hands-on experience with knowledge graph technologies and graph databases like Neo4j, ArangoDB, or similar.
Familiarity with large language models (LLMs) and their application in business contexts.
Leadership Skills: Proven ability to lead cross-functional teams, manage complex projects, and drive AI initiatives from concept to deployment.
Strategic Thinking: Ability to align AI strategies with business objectives and navigate the complexities of integrating autonomous systems into organizational workflows.
Industry Experience: Experience in insurance sectors, where the integration of AI agents and knowledge graphs can drive significant impact.
 

Preferred Qualifications:

Advanced Certifications: Certifications in AI/ML, data science, or related fields from recognized institutions.