AI Engineer – Conversational AI and Prompt Engineering
2 weeks ago
We are seeking an experienced AI Engineer who will play a pivotal role in developing and deploying advanced conversational bots to elevate customer interactions for our clients. The ideal candidate will design and refine AI-driven conversational experiences, focusing on enhancing the user's journey across various platforms, especially through WhatsApp. Your responsibilities will include crafting effective conversation scripts, testing and refining user journeys, and ensuring seamless bot interactions with human agents. You will collaborate with cross-functional teams to integrate AI tools and optimize chatbot workflows, driving better engagement, sales productivity, and operational efficiencies.
This role offers the opportunity to be part of a dynamic team at the intersection of AI, digital marketing, and customer experience.
- Design and Develop Conversational Scripts and User Flows:
- Create, optimize, and implement conversation scripts and user journeys for AI-driven chatbots. Focus on aligning the dialogues with the target personas and ensuring smooth user interactions.
- Designing Engaging Bot Responses with Personality:
- Develop engaging and human-like bot responses by infusing personality, tone, and context into conversations, ensuring a smooth flow of interactions and providing accurate, helpful, and user-friendly responses.
- Building User Journeys Based on Different Personas:
- Tailor user journeys to specific bot personas, considering user behaviors and preferences. Ensure that the flow is optimized for different interaction styles and that each user’s journey results in the desired outcomes.
- Enhancing User Experience through Conversational Flow Creation:
- Collaborate with product managers and UX/UI teams to design intuitive and engaging conversational flows. Build bots that respond dynamically based on user inputs, offering flexibility and personalization.
- Integrating and Leveraging AI Tools and Platforms:
- Use WA and LLM platforms like Botpress, and Flowise to build and deploy chatbots that enhance user experience. Experience with these platforms will help in designing effective workflows and streamlining chatbot deployment across various channels.
- Leveraging Large Language Models (LLMs):
- Incorporate LLMs like GPT-3, Claude, and Gemini into the conversational design to improve user engagement and operational efficiency. Ensure that AI models are continually optimized for accuracy, creativity, and relevance.
- Optimizing Prompts for AI Models:
- Design, refine, and optimize prompts for AI models to ensure the generation of accurate, relevant, and context-aware responses. Continuously improve the prompts based on user feedback and ongoing performance analysis.
- Evaluate and Optimize AI Model Outputs:
- Regularly assess AI-generated responses and make adjustments to prompts or models. Use feedback, analytics, and testing to improve bot performance and enhance user interactions.
- A/B Testing and Experimentation:
- Conduct A/B tests to evaluate different conversational approaches and AI strategies. Refine the models based on testing results to ensure the highest level of effectiveness in user engagement.
- Collaborate with Cross-Functional Teams:
- Work closely with developers, product managers, and UX/UI designers to ensure smooth integration of AI models and conversational AI tools with existing systems and applications. Collaborate on implementing AI features that improve the overall user experience.
- Training and Support:
- Provide training and support to internal teams to ensure they are effectively utilizing AI platforms like Gupshup, WAti, and Botpress. Help teams fully leverage these tools for optimal performance and integration.
- Monitor AI Model Performance and Fine-Tune:
- Continuously monitor AI performance and use data-driven insights to fine-tune the models. Ensure AI models adapt to evolving user needs and continue to improve the quality of interactions.
- Research Best Practices in Conversational AI and Prompt Engineering:
- Stay up to date with the latest trends in conversational AI, prompt engineering, and NLP. Apply best practices and emerging techniques to ensure AI models stay cutting-edge and deliver the best outcomes.
- 3 to 5 years of experience in AI engineering, NLP, or chatbot development.
- Educational Background: Bachelor’s degree in Computer Science, Math, or a related field.
- Technical Expertise: Proficiency in Python and familiarity with AI/ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
- Conversational AI Platform Experience: Hands-on experience with platforms like WA API and Botpress, and Flowise for building and deploying AI-powered chatbots.
- Experience: Proven experience in Prompt Engineering and NLP, particularly with large language models such as GPT-3, BERT, or similar frameworks.
- AI/ML Experience: Experience in building, training, and deploying machine learning models with a focus on NLP and AI applications.
- API Integration: Experience with integrating APIs to connect AI models to applications, preferably using REST or GraphQL.
- Analytical Skills: Strong ability to evaluate AI outputs, iterate on designs, and experiment to improve model performance.
- Cloud Platforms: Familiarity with cloud platforms like AWS, Google Cloud, or Azure for deploying AI/ML solutions.
- Version Control: Experience with Git or other version control systems.
- Communication: Strong written and verbal communication skills to collaborate with both technical and non-technical teams.
- Work remotely with flexible hours.
- Be at the forefront of AI-driven innovations in conversational technology.
- Competitive compensation with opportunities for career growth.
- Collaborative work environment with exposure to diverse AI projects.
- The freedom to experiment with the latest AI tools and technologies.
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