Product Builder – Conversational AI

Responsibilities

• 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.

Requirements

• 2–7 years of experience in product management, product engineering, or a hybrid role at a Saa S or enterprise software company, with a demonstrated track record of shipping product to production.
• Hands‑on building capability — sufficient to prototype, deploy, and iterate on features independently; proficiency in at least one programming language (Python preferred) and comfort working directly in codebases.
• Meaningful experience with conversational AI, voice or IVR platforms, contact centre technology, speech applications, or chatbot development; exposure to the contact centre domain is a genuine advantage.
• Fluency with AI/LLM concepts: prompt engineering, RAG architectures, intent classification, and agentic workflow design.
• Developer experience thinking: API design principles, flow builder ergonomics, documentation quality, and structured onboarding — particularly in no‑code/low‑code and agentic environments.
• Data literacy sufficient to interpret usage analytics, build lightweight dashboards, and pressure‑test product assumptions without relying on a dedicated data team.
• Working knowledge of Jira, Confluence, Git, and Agile/Scrum delivery practices.
• (Nice to have) Exposure to Lang Graph, Lang Chain, or MCP (Model Context Protocol); Agile/Scrum certification (PSPO, CSPO, or equivalent).
• Bachelor’s degree in Computer Science, Software Engineering, Computational Linguistics, Digital Humanities, or a related field; equivalent professional experience considered in lieu of formal qualification.
• Business‑level fluency in English (written and spoken) is mandatory.
• Additional European languages (Greek, Italian, German, French, Spanish) are an asset.
• #J-18808-Ljbffr