Lead AI Solutions Architect

Be the one building AI-powered experiences where they matter most.   At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.   Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day. Genesys is seeking a hands-on Conversational AI Engineer to build, optimize, and continuously improve Virtual Agents and Agentic Virtual Agents on Genesys Cloud. In this role, you will combine NLU development, prompt engineering, data analysis, and customer collaboration to improve the reliability and effectiveness of automated customer experiences in production. You will work deeply with real-world conversation data, iteratively refining NLU models and LLM prompts while partnering with customers and cross-functional teams to translate business requirements into measurable improvements. This is an opportunity to directly influence how AI-powered experiences perform at scale while embracing empathy, collaborating across teams, and thinking big about the future of conversational AI.

Agentic Virtual Agent Configuration and Tuning Design and develop prompts for Agentic Virtual Agents that drive reliable task completion and high-quality customer experiences. Structure prompts to support appropriate grounding, tool and API usage, orchestration, and response consistency. Analyze failures in LLM-driven interactions and identify root causes across prompts, orchestration, data, and system behavior. Refine prompts iteratively to improve reliability, edge-case handling, task completion, and user experience. Evaluate end-to-end performance across NLU and LLM layers and implement data-driven optimizations. Establish and apply evaluation frameworks and test methodologies that support continuous improvement of agentic systems. NLU Development Design and build NLU models, including intents, entities, and utterances, that reflect real user behavior and business requirements. Define scalable intent taxonomies and entity structures that support model accuracy, maintainability, and future growth. Create and curate high-quality training data to improve model coverage, precision, and accuracy. Translate customer requirements and conversation patterns into effective conversational AI designs. NLU Analysis and Optimization Analyze production conversation logs to identify misclassifications, false positives, coverage gaps, and edge cases. Optimize post-launch NLU performance through updates to training data, intent structures, and entity recognition. Develop and execute scripts that support analysis, evaluation, and efficient implementation of NLU model improvements. Measure and track NLU performance using defined evaluation metrics, test sets, and production data. Communicate performance findings, recommendations, and measurable improvements to customers and internal stakeholders.

Bring a master's degree in Computer Science, Data Science, Machine Learning, or a related technical field. Demonstrate 3 to 5 years of experience working with conversational AI, generative AI, NLU, NLP, or related language technologies. Apply Python and Node.js experience to data preparation, analysis, evaluation, automation, and model tuning. Demonstrate experience working with Genesys Cloud, another CCaaS platform, or a conversational AI platform. Apply hands-on experience developing, evaluating, or optimizing NLU models and LLM-based conversational experiences. Analyze complex conversational AI performance issues and translate findings into actionable improvements. Present technical findings, recommendations, and performance results clearly to customers and stakeholders. Work