AI Solutions Architect

What You’ll Do

Discovery and Strategy Alignment

• Partner with Genesys CX Advisors, Solution Consultants, and customer stakeholders to identify AI use cases aligned with strategic objectives
• Assess value, effort, and feasibility to prioritise initiatives effectively
• Translate customer KPIs (AHT, CSAT, containment rates, etc.) into actionable AI solution opportunities

Design and Architecture

• Define reference architectures, integration patterns, and data flows for AI-powered experience orchestration
• Lead process‑redesign workshops to create seamless, channel‑agnostic CX
• Ensure all designs comply with Genesys and customer security, privacy, and regulatory requirements (GDPR, PDPA, PCI, HIPAA where applicable)

Prototype and Implementation

• Deliver rapid POC and MVP implementations using Genesys Cloud AI Studio, CoPilot, Agentic Virtual Agent, and related product suites
• Integrate Genesys AI components with customer CRM, ERP, and third‑party systems
• Establish implementation KPIs and analytics to measure model and journey performance

AI Engineering & Outcome‑Oriented Delivery

• Design and implement evaluation frameworks to measure AI solution quality in production: intent accuracy, retrieval groundedness, response relevance, agent goal completion, and policy adherence
• Build automated eval pipelines that enable rapid, systematic iteration across prompt variants, guardrail configurations, and model versions — treating evals as a continuous improvement mechanism, not a one‑time QA gate
• Apply knowledge engineering methods to assess and optimise knowledge bases for AI consumption: groundedness checks, semantic coverage analysis, retrieval relevance scoring, and LLM-based preprocessing to transform raw content into formats that perform in production
• Architect agentic systems with precision, instrument deployments using AI observability tooling, measure success through production adoption and demonstrable outcome improvement

Optimisation and Continuous Improvement

• Evaluate solution performance against KPIs and refine designs based on data‑driven insights
• Collaborate with Customer Success and Professional Services teams to hand over production‑ready assets and roadmaps
• Document best practices and reusable accelerators to strengthen future deployments

Governance, Ethics, and Enablement

• Champion responsible AI design principles and apply guardrails to prevent bias or unsafe responses
• Adhere to Genesys ethical standards and compliance frameworks
• Mentor customer and partner teams to build long‑term AI maturity and self‑sufficiency

What We’re Looking For

• Proficiency in both French and English is required.
• Bachelor’s degree (Master’s preferred) in Computer Science, Information Technology, Data Science, or a related discipline
• 8–12 years of combined experience across AI implementation, CX/CCaaS platform consulting, or technical solution architecture — demonstrated through overlap and measurable customer impact, not additive year counts across separate tracks
• At least five years of experience implementing or supporting CX, CRM, or AI orchestration platforms (e.g., Genesys Cloud, Google CCAI, Salesforce, Microsoft, NICE CXone, AWS Connect, ServiceNow, or similar)
• Hands‑on experience with agentic AI systems: building, evaluating, or operating LLM‑powered agents in production contexts
• Demonstrated experience working with APIs, data pipelines, and modern cloud environments (AWS, Azure, GCP)
• Track record of mentoring or developing technical peers and codifying expertise into approaches others can build on

Technical Skills

• CX orchestration and workflow design across multiple platforms
• Conversational AI and Agentic Virtual Agent implementation across voice, chat, and messaging channels
• AI evaluation frameworks: design and execution of groundedness, relevance, goal completion, and policy adherence evals.
• Knowledge engineering: retrieval system diagnosis, RAG pipeline design, semantic coverage analysis, and knowledge optimisation for AI consumption
• Agentic system design: tool schema authoring, multi‑agent topology, prompt engineering as a systematic discipline, and guardrail implementation for enterprise‑safe agent behaviour
• Applied data analysis: Python for evaluation scripting, log analysis, and integration development; SQL for operational data querying and pattern identification — AI‑assisted development tooling is expected and encouraged
• Data and integration expertise: REST APIs, event‑driven architecture, JSON
• Cloud infrastructure familiarity: provisioning, access control, and cost management (AWS preferred)
• Data governance, security compliance, and responsible AI design principles

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.