What are the responsibilities and job description for the Lead GenAI Engineer - Onsite position at Acunor?
Job Title: Lead GenAI
Location: Charlotte, NC (onsite)
Experience: 14 years
Key Responsibilities
Location: Charlotte, NC (onsite)
Experience: 14 years
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.
- 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.
- Advanced Certifications: Certifications in AI/ML, data science, or related fields from recognized institutions.
