Software Engineer (Conversational AI Application Developer) Tech Lead

🏢 Omilia · all 32 jobs
📍 Brazil
📅 Posted Sep 16, 2026 · via WorkableBoard
🏷 Remote
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The Tech Lead, Conversational AI Application Developer owns end-to-end solution design and technical direction for the agentic implementation. This role bridges business requirements and hands-on execution, defining how autonomous agents are scoped, how task handoffs are structured, where human escalation thresholds are set, and how the development team is coordinated.
Accountabilities
- Solution Ownership: Accountable for end-to-end solution design and technical direction of the agentic implementation, from business requirements through to production delivery.
- Team Leadership: Accountable for leading and coordinating the project team of Conversational AI Application Developer(s), QA Engineer, and Integrations Engineer.
- Delivery Quality: Accountable for the quality, KPI alignment, and timely delivery of the conversational AI application.
- Escalation & Autonomy Design: Accountable for defining how autonomous agents are scoped, how task handoffs are structured, and where human escalation thresholds are set.
- Stakeholder Management: Accountable for client consultation and for communication with internal and external stakeholders throughout delivery.

Key Responsibilities
- Lead a project team of Conversational AI Developers responsible for the design, development, and delivery of production-grade conversational AI applications using Omilia's technology suite.
- Analyse business requirements and design and develop the solution to meet those requirements.
- Ensure the application aligns with established usability principles and meets set KPIs.
- Manage the team's backlog; assign and oversee project-related tasks.
- Ensure the quality and timely delivery of the application.
- Consult customers and provide guidance on problem resolution and best practices.
- Explain the technology and application capabilities to clients and stakeholders.
- Identify and communicate improvement opportunities.
- Communicate with internal and external stakeholders on progress, risks, and technical decisions.
- Define escalation thresholds and task-handoff structures between autonomous agents and human agents.

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