Job Summary We are seeking an experienced AI Director to build a department that can implement chatbots, voice bots, and SMS bots for a variety of small and medium-sized businesses. The ideal candidate should be proficient in several areas that span technical skills, AI-specific expertise, team management, and business acumen.
Job Requirements Technical Proficiency in AI and Machine Learning: Natural Language Processing (NLP): The expert should have a deep understanding of NLP technologies, as chatbots and voice bots rely on the ability to interpret and generate human language. Proficiency with NLP Libraries: Familiarity with TensorFlow, PyTorch, spaCy, Hugging Face, and other libraries commonly used for NLP tasks. Chatbot Frameworks: Experience working with frameworks like Dialogflow, Rasa, Amazon Lex, and Microsoft Bot Framework for building conversational interfaces. Machine Learning: Expertise in machine learning, including supervised, unsupervised, and reinforcement learning techniques, is crucial for developing and optimizing AI models. Voice Recognition: Familiarity with speech-to-text and text-to-speech technologies for building voice bots, using tools like Google Cloud Speech-to-Text, Amazon Polly, or Azure Cognitive Services. Knowledge of Algorithms: Proficiency in understanding and implementing various ML algorithms, such as classification, clustering, deep learning, and transformer models (e.g., GPT, BERT). Programming Skills Python: Python is the primary programming language for most AI applications, especially with libraries like scikit-learn, pandas, and NumPy. JavaScript: Knowledge of JavaScript is also important for integrating bots into web environments, especially using tools like Node.js. Backend Development: Understanding of backend technologies to integrate AI bots with databases, APIs, and external systems. Familiarity with RESTful APIs, GraphQL, and SQL/NoSQL databases (e.g., MongoDB, PostgreSQL) is beneficial. Conversational AI Design: Conversational Flow Design: Expertise in designing effective conversational flows for chatbots and voice bots, focusing on providing users with seamless and engaging interactions. Multichannel Integration: Experience in integrating AI with multiple communication channels, including SMS, social media platforms (e.g., Facebook Messenger, WhatsApp), and voice assistants like Amazon Alexa or Google Assistant. Deployment and Cloud Platforms: Cloud Infrastructure: Experience with deploying and managing AI applications in cloud environments like AWS, Google Cloud, or Microsoft Azure. Understanding of serverless architecture (e.g., AWS Lambda) and container orchestration (e.g., Docker and Kubernetes) is also valuable. Scalability and Performance: The ability to design AI systems that are scalable to handle multiple clients across different industries. Experience with Integration and Automation: CRM and ERP Integration: Experience integrating chatbots and automation tools into existing CRM systems like Salesforce, HubSpot, or Zoho, as well as ERP systems, to streamline communication processes for small businesses. RPA (Robotic Process Automation): Familiarity with RPA tools, such as UiPath or Blue Prism, to automate business processes that interact with chatbots. Project Management and Team Building: Team Leadership: Ability to build, manage, and mentor a team of developers, data scientists, and UI/UX designers, fostering collaboration and ensuring the department's goals are met. Agile Methodology: Familiarity with Agile methodologies for effective project management, allowing for rapid iterations and adjustments. Cross-functional Collaboration: Experience working with sales, marketing, and customer service teams to understand business requirements and tailor AI solutions accordingly. Business Acumen and Understanding of SMB Needs: Knowledge of SMB Challenges: An understanding of the unique challenges faced by small and medium-sized businesses, such as budget constraints and the need for efficient customer support solutions. ROI-Focused Approach: Ability to frame AI solutions in terms of their impact on the business's bottom line, demonstrating cost-effectiveness and value. Customization and Flexibility: The ability to create flexible AI solutions that can be customized for different industries—whether it's retail, healthcare, or professional services. Data Privacy and Compliance: GDPR/CCPA Compliance: Proficiency in ensuring that all AI solutions comply with relevant data privacy laws such as GDPR (General Data Protection Regulation) or CCPA (California Consumer Privacy Act). Data Security: Experience with implementing data security measures to protect user data, ensuring secure communication between bots and clients. Qualifications: AI and ML Certifications: Certifications such as Google Professional Machine Learning Engineer, AWS Certified Machine Learning, or other recognized ML certifications can demonstrate a strong foundational knowledge of AI technologies. Relevant Work Experience: Hands-on experience in building chatbots, voice bots, or customer service automation in a similar setting, preferably across different business sizes and industries. Advanced technical proficiency in AI, NLP, machine learning, and conversational bot frameworks. Programming and integration skills for multi-channel and CRM integrations. Experience with cloud platforms for deployment and scalability. Team leadership and business understanding of how AI can create value for small and medium-sized businesses. Compliance knowledge for data privacy and security. Job Type: Full-time
Benefits: Opportunities for promotion Work from home Schedule: 8 hour shift Evening shift Experience: AI: 5 years (Preferred)
#J-18808-Ljbffr