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Genesys

Lead AI Solutions Architect

Genesys

. Design and develop prompts for Agentic Virtual Agents to drive reliable task completion and high-quality customer experiences .

Posted 10/8/2026full-timeRemote • United StatesSenior💰 $110,600 - $194,400 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and optimizing NLU models and conversational AI systems, with a strong focus on performance evaluation and data-driven improvements. Proficient in prompt engineering and capable of translating customer requirements into effective conversational designs.

Highest-signal resume keywords
Conversational AI DevelopmentNLU Model OptimizationPrompt EngineeringPython ProgrammingData Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Natural Language UnderstandingMachine LearningGenerative AIEvaluation FrameworksTest-Set DevelopmentIntent Taxonomy DefinitionEntity RecognitionData PreparationModel TuningPerformance Measurement
Soft Skills
Technical CommunicationCollaborationProblem-SolvingIndependent WorkStakeholder Engagement
Tools & Technologies
Genesys CloudCCaaS PlatformsConversational AI PlatformsNode.jsLLM Technologies
Certifications & Qualifications
Master's Degree in Computer ScienceMaster's Degree in Data ScienceMaster's Degree in Machine Learning
Industry Keywords
Conversational AINLUNLPTask CompletionUser ExperienceData-Driven OptimizationPerformance EvaluationEdge-Case HandlingTraining Data CurationProduction Conversation Analysis

Tech Stack

Tools & technologies
CloudJavaScriptNode.jsPython

About the role

Key responsibilities & impact
  • Design and develop prompts for Agentic Virtual Agents to drive reliable task completion and high-quality customer experiences
  • Structure prompts for 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 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 for continuous improvement of agentic systems
  • Design and build NLU models, including intents, entities, and utterances
  • Define scalable intent taxonomies and entity structures
  • Create and curate training data to improve model coverage, precision, and accuracy
  • Translate customer requirements and conversation patterns into conversational AI designs
  • Analyze production conversation logs for misclassifications, false positives, coverage gaps, and edge cases
  • Optimize post-launch NLU performance through training data, intent structure, and entity-recognition updates
  • Develop and execute scripts for NLU analysis, evaluation, and model improvements
  • Measure and track NLU performance using evaluation metrics, test sets, and production data
  • Communicate performance findings, recommendations, and measurable improvements to customers and internal stakeholders
  • Collaborate with engineering, product, customer-facing, and cross-functional teams

Requirements

What you’ll need
  • Master's degree in Computer Science, Data Science, Machine Learning, or a related technical field
  • 3 to 5 years of experience working with conversational AI, generative AI, NLU, NLP, or related language technologies
  • Python and Node.js experience for data preparation, analysis, evaluation, automation, and model tuning
  • Experience working with Genesys Cloud, another CCaaS platform, or a conversational AI platform
  • Hands-on experience developing, evaluating, or optimizing NLU models and LLM-based conversational experiences
  • Ability to analyze complex conversational AI performance issues and translate findings into actionable improvements
  • Ability to present technical findings, recommendations, and performance results clearly to customers and stakeholders
  • Ability to work independently while collaborating effectively with engineering, product, customer-facing, and other cross-functional teams
  • Hands-on experience with prompt engineering and evaluation techniques for LLM-powered or agentic AI systems
  • Experience analyzing production conversation data and improving post-launch conversational AI performance
  • Experience with evaluation frameworks, test-set development, experimentation, or performance measurement for AI systems
  • Professional communication in Spanish in addition to English

Benefits

Comp & perks
  • Medical, Dental, and Vision Insurance
  • Telehealth coverage
  • Flexible work schedules and work from home opportunities
  • Development and career growth opportunities
  • Open Time Off
  • 10 paid holidays
  • 401(k) matching program
  • Adoption Assistance
  • Fertility treatments
  • Mentorship, learning programs, leadership development and education support
  • Paid volunteer time
  • August Free Fridays
  • Well-being resources
  • Regionally tailored programs for employees and their families