▷ [Apply in 3 Minutes] Conversation AI Engineer

Job Description Key Responsibilities - Training and enablement for IVA Studio, ensuring users understand and adopt the tool effectively for their immediate business needs and future goals. - Collaborate with Sales and Product teams talign learning initiatives with departmental goals and customer needs. - Build strategic partnerships with internal teams tco-create innovative learning solutions. - Troubleshoot challenges with customers, partners and internal teams and provide guidance toptimize their IVA solutions and encourage self-sufficiency. - Document processes, learning materials, and strategies with clarity and precision for all different levels. - Experiment with latest product releases and emerging technologies tcontinuously improve personal expertise and future learning experiences. - Develop and deploy solutions leveraging Large Language Models (LLMs) such as GPT, Claude, or open-source alternatives for enterprise use cases. - Design and implement Retrieval-Augmented Generation (RAG) pipelines tenhance LLM performance with domain-specific knowledge. - Apply Model Customization & Prompting (MCP) techniques including fine-tuning, prompt engineering, and instruction tuning toptimize model outputs. - Build and orchestrate Agentic AI systems, enabling autonomous agents tplan, reason, and act in complex environments. - Design and manage Agent-to-Agent (A2A) communication protocols for collaborative multi-agent systems. - Collaborate with cross-functional teams tintegrate AI capabilities intproducts and services, ensuring scalability and reliability. - Stay current with advancements in generative AI, agent frameworks (e.g., LangChain, AutoGen, CrewAI), and foundation model APIs. - Evaluate and benchmark LLM performance using metrics such as factuality, coherence, latency, and cost-efficiency. - Ensure ethical and responsible AI practices, including bias mitigation, explainability, and data privacy. Required Skills & Capabilities - Conversational AI Implementation: Proven success in deploying and supporting real-world IVA solutions. - AI Fluency: Strong understanding of AI technologies with a proactive approach texperimentation and integration intIVA/IVR. - Programming Familiarity: Comfortable with coding and scripting (especially JavaScript, Python, MQL) tsupport problem solving, optimization, and technical understanding in IVA Studio. - Technical Translation: Skilled at translating complex technical language intclear, practical guidance for diverse audiences. - Instructional Design & Enablement:Ability tcreate engaging, effective learning experiences tailored tuser needs and business goals. - Documentation:Ability tcreate clear, comprehensive, and scalable documentation. - Cross-Functional Collaboration: Deep understanding of the goals, workflows and communication styles of Sales, Product, and Delivery. - User Enablement Expertise: Experienced in consulting, troubleshooting, and guiding users through change with a focus on building confidence and independence. - Strong understanding of transformer architectures and LLM internals. - Experience with vector databases (e.g., FAISS, Pinecone, Weaviate) for RAG implementations. - Familiarity with agent frameworks and orchestration tools. - Proficiency in Python and ML libraries (e.g., Hugging Face, LangChain, OpenAI SDK). - Prior experience in deploying AI solutions in production environments. Recommended Soft Skills & Qualities - Empowerment-Focused Training: Committed thelping people work independently, not just doing work for them. - Patience & Support: Approaches learning and troubleshooting with understanding and calm persistence. - Fearless Experimentation: Willing ttry new approaches and technologies, embracing failure as part of growth. - Optimistic Problem-Solving: Tackles challenges with a why notattitude, followed by thoughtful research tfind the best solution. - Curiosity & Innovation: Constantly seeks better ways tteach, communicate, and connect IVA capabilities treal-world needs.