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.

Key Responsibilities

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.

Qualifications

• 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 independently while collaborating effectively with engineering, product, customer-facing, and other cross-functional teams.

Preferred Qualifications

• Bring hands-on experience with prompt engineering and evaluation techniques for LLM-powered or agentic AI systems.
• Demonstrate experience analyzing production conversation data and improving post-launch conversational AI performance.
• Apply experience with evaluation frameworks, test-set development, experimentation, or performance measurement for AI systems.
• Communicate professionally in Spanish in addition to English

#LI-CP1 #LI-Remote

Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.

Benefits:

• Medical, Dental, and Vision Insurance.

• Telehealth coverage

• Flexible work schedules and work from home opportunities

• Development and career growth opportunities

• Open Time Off in addition to 10 paid holidays

• 401(k) matching program

• Adoption Assistance

• Fertility treatments

Click here to view a summary overview of our Benefits.

Working at Genesys

• AI at enterprise scale – Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+ new AI features were released in the last fiscal year.
• A flexible-first culture – Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work.
• Growth in the AI era – Build future-ready skills through mentorship, learning programs, leadership development and education support.
• Time to recharge and give back – Benefits include paid volunteer time, August Free Fridays, well-being resources and regionally tailored programs for employees and their families.
• Recognized globally – Genesys is Great Place to Work® certified in 17 countries and 94% of employees are proud to tell others they work at Genesys.

Learn more about our culture, AI innovation and sustainability commitments through our Careers site and Sustainability Report.

What Happens After You Apply

After you apply, here's what you can typically expect:

• Our Talent Acquisition team reviews your application with the hiring team.

• A Talent Acquisition Partner will review your application and, if your background is aligned, schedule a Zoom interview.

• Next, you'll meet the hiring manager and other members of the interview team.

• We aim to keep the process focused and respectful of your time, with no more than five interviews in most cases.

• After interviews are complete, our team will follow up with the final steps.

Every application is reviewed by a person. Response times may vary by role and location, but our team will keep you informed throughout the process.

Stay Connected

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Be the one building what's next - where AI, experience and impact come together.

Employee Referral

If a Genesys employee referred you, please apply using the link they shared so we can connect your application to their referral.

About Genesys:

Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. Genesys Cloud™ is the Agentic Orchestration Platform that securely connects people, systems, data and AI across the enterprise with built-in governance and control. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visit

Reasonable Accommodations:

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Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, marital status, domestic partner status, national origin, genetics, disability, military and veteran status, and other protected characteristics.

Please note that recruiters will never ask for sensitive personal or financial information during the application phase.