Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences at scale to drive customer loyalty, workforce engagement, efficiency and operational improvements.
We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed. And, while we offer great benefits and perks like larger tech companies, our employees have the independence to make a larger impact on the company and take ownership of their work. Join the team and create the future of customer experience together.
As a Forward Deployed Engineer at Genesys, you will serve as the strategic and technical bridge between customer ambition and successful AI transformation.
You will partner directly with strategic customers across the EMEA region to design, prototype, and operationalise Genesys AI solutions that drive measurable improvements in customer experience and business performance. At Genesys, we're transforming how organisations connect with their customers through empathy, collaboration, and innovation.
This role offers the opportunity to make a lasting impact by helping enterprises move from AI exploration to continuous transformation — and to shape how that transformation capability is built and scaled within the organisation.
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, nstrument 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
Experience
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
Business and Soft Skills
Strong analytical and critical thinking skills, able to bridge technical and business domains
Excellent communication and stakeholder engagement skills, able to influence executive audiences and drive alignment on AI strategy
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