Artificial Intelligence

• Own client configuration and deployment of Emiri (AI solution)
• Understand and support Emiri’s configuration dependencies, including prompt templates and setup requirements
• Design UI mockups or flow diagrams and translate feedback into actionable stories or bug reports for the development team
• Document and maintain guidance around configuration processes, tips, and “how-to” documentation for internal use
• Collaborate with client success and client teams to support their understanding of configuration needs and guiding them in effective prompting
• Drive root cause analysis of issues to surface opportunities to improve scalability and user friendliness of the configuration tool
• Coach commercial teams on the configuration and functionality of Liquid AI; support key client meetings and demos
• Test new enhancements or fixes prior to release to ensure quality and expected behavior

AI Configuration Specialist

• Design and develop machine learning models and algorithms for various aspects of the localization and business workflow processes, including machine translation, LLM finetuning, and quality assurance
• Take ownership of key projects from definition to deployment, ensuring that they meet technical requirements and maintain momentum and direction until delivery
• Evaluate and select appropriate machine-learning techniques and algorithms to solve specific problems
• Implement and optimize machine learning models and technologies using Python, TensorFlow, and other relevant tools and frameworks
• Perform statistical analysis and fine-tuning using test results
• Deploy machine learning models and algorithms using appropriate techniques and technologies, such as containerization using Docker and deployment to cloud infrastructure
• Use AWS technologies (including but not limited to Sagemaker, EC2, S3) to deploy and monitor production environments
• Document diligently and communicate thoughtfully about ML experimentation, design, and deployment

AI/ML R&D Engineer

• Own assigned OCP product areas end-to-end — from problem definition and prototyping through to production delivery.
• Drive platform adoption by shipping working, validated solutions rather than specifications alone.
• Deliver measurable reduction in friction across the OCP builder journey, using usage data and field feedback as the primary inputs.
• Operate autonomously within the Developer Experience pod, minimising delivery dependencies on broader engineering cycles for tasks within scope.
• Act as a credible product voice in cross-functional reviews, customer escalations, and internal stakeholder conversations when required.
• Align with Product leadership on roadmap priorities and contribute to the iterative shaping of the Developer Experience pod’s direction.
• Define user stories, acceptance criteria, and success metrics for assigned Developer Experience areas within OCP.
• Ship features autonomously — from idea generation through to production — using AI-coding tools to accelerate exploration and internal tooling.
• Validate hypotheses with working software before committing full engineering cycles; favour fast, evidence-based iteration over extensive upfront specification.
• Identify and eliminate friction points in the OCP builder journey by synthesising usage data, field feedback, and direct observation of how Omilia teams, partners, and customer configurators interact with the platform.
• Prioritise backlog items based on builder impact, platform scalability, and delivery feasibility; manage the trade-offs between speed and quality with sound judgement.
• Collaborate actively with engineering squads on features that exceed individual scope; provide clear product direction and unblock delivery without micromanaging execution.
• Contribute to the evolution of agentic application design patterns on OCP as the platform’s AI capabilities expand.
• Represent the product in customer-facing contexts as needed — including escalation calls and product reviews — articulating decisions and roadmap direction with clarity.
• Maintain documentation standards in Confluence and Jira sufficient for engineering partners and the wider Product team to build on your work.

Product Builder – Conversational AI

• Own technical delivery quality from design through go-live and hypercare — ensuring on-time, on-budget outcomes aligned with client CX goals.
• Serve as the primary technical point of contact for assigned client engagements — translating business requirements into technical architectures and CX designs.
• Proactively identify and manage delivery risks, escalate complex technical issues, and drive resolution with urgency.
• Provide technical guidance and mentorship to junior engineers within the delivery team.
• Contribute to internal delivery accelerators, tooling, reusable solution components, and best-practice documentation.
• Collaborate across Solution Delivery, Product, Platform, R&D, Sales, Pre-Sales, and Certified Partners to ensure alignment on project requirements and Omilia platform capabilities.
• Design, configure, and deploy end-to-end conversational AI solutions on the Omilia OCP platform — covering agentic workflows blended with traditional NLU modelling, and omnichannel integrations.
• Integrate GenAI capabilities into production deployments — including RAG pipelines, embedding search, and LLM prompt engineering.
• Manage contact centre infrastructure integrations: IVR, SIP, CTI, and omnichannel APIs.
• Serve as the primary technical point of contact for assigned client engagements — translating business requirements into technical architectures and CX designs, and maintaining trusted relationships with customers and partners throughout the project lifecycle.
• Collaborate closely with Solution Architects, Product, Platform, R&D, and Pre-Sales to ensure alignment on project requirements and Omilia platform capabilities.
• Proactively identify and manage delivery risks — escalating complex technical issues and driving resolution with urgency.
• Provide technical guidance and mentorship to junior engineers within the delivery team.
• Contribute to internal delivery accelerators, tooling, reusable solution components, and best-practice documentation.
• Actively research developments in conversational AI, agentic frameworks, and GenAI tooling to drive continuous improvement in delivery processes.
• Foster a culture of quality, innovation, and ownership within the team.

Artificial Intelligence jobs in Greece

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AI Configuration Specialist

AI/ML R&D Engineer

Product Builder – Conversational AI

Senior Conversational AI Delivery Engineer