WPP is looking to help B2B clients successfully adopt and leverage AI agents and sophisticated prompt engineering techniques to achieve their business goals, driving user adoption, identifying opportunities for improvement, and establishing best practices.
Requirements
- Significant of experience in AI, machine learning, or natural language processing.
- Proven experience in prompt engineering and AI agent development.
- Strong understanding of AI concepts, algorithms, and machine learning techniques.
- Experience with programming languages such as Python, Java, or C++.
- Familiarity with AI agent frameworks and platforms (e.g., OpenAI Gym, TensorFlow Agents, Rasa).
- Experience with data analysis, data mining, and knowledge representation.
- Familiarity with AI models, programming languages (e.g., Python), and data analysis.
Responsibilities
- Define the goals, capabilities, and functionalities of AI agents for specific client use cases.
- Design the agent's architecture, including data input/output, decision-making processes, and interaction mechanisms.
- Identify and define tasks that can be automated by AI agents to augment teams on project-based pilots, driving early value realization.
- Monitor agent performance and identify areas for improvement, leveraging data-led insights to unlock operational efficiencies.
- Develop Agents evaluation dataset and perform Agents testing
- Implement mechanisms for agents to learn from data and adapt to changing environments.
- Deploy AI agents in a production environment and monitor their performance.
Other
- Collaborate with other teams to ensure seamless integration and deployment.
- Contribute to end-user materials preparation, including playbooks, videos and reference guides.
- Identify user pain points and opportunities for continuous improvement to the product backlog.
- Collaborate with cross-functional teams, including product development, customer success, and sales, to ensure alignment and coordination of efforts.
- Excellent communication skills to collaborate effectively with cross-functional teams.
