Conversational AI Application Developer (English and French Speaker)

The Software Engineer (Conversational AI Application Developer), Mid develops, implements, and maintains high-quality conversational AI applications on the Omilia Cloud Platform (OCP). Compared with Junior, Mid carries more ownership of customer requirements gathering, application design, and internal mentoring / task coordination as experience grows — and is expected to gain confidence in Omilia’s stack faster when hired at Mid. The role ensures seamless user experiences and robust technical performance across enterprise client deployments, working within a squad under a Team Lead or Solution Delivery Manager.

Accountabilities

• Feature Ownership: Accountable for the end-to-end development and unit testing of specific conversational features and miniApps.
• Technical Execution: Ownership of the implementation of business logic and conversational flows as defined in Detailed Design Specifications (DDS).
• NLU Management: Accountable for the creation, uploading, and basic tuning of NLU models and resources.
• System Stability: Ownership of troubleshooting and resolving defects identified during QA, UAT, or production hypercare phases.
• Environment Management: Accountable for the successful deployment and promotion of applications across OCP environments (Dev, UAT, Prod).

Key Responsibilities

• Write clean, maintainable code to build conversational dialogs, integrating with backend web services and CCaaS platforms.
• Prepare and upload NLU training data, manage intent selection policies, and ensure high concept identification success rates.
• Perform rigorous unit testing and use tools like ELK/Kibana to analyse logs and resolve runtime errors.
• Maintain technical documentation for implemented features and contribute to master prompt lists and implementation steps.
• Participate in daily stand-ups and sprint planning, providing accurate task estimates and surfacing technical risks early.
• Manage application deployments and promotions across OCP environments, following Omilia's change management protocols.

The Software Engineer (Conversational AI Application Developer), Mid develops, implements, and maintains high-quality conversational AI applications on the Omilia Cloud Platform (OCP). Compared with Junior, Mid carries more ownership of customer requir...

Required:

• Strong hands-on experience with the Omilia Cloud Platform (OCP) and its core components — Dialog Manager, NLU, miniApps, or hands-on experience in production-grade development with other Conversational AI Platforms.
• Solid background in software development, including JavaScript/Node.js and working with RESTful APIs and JSON.
• Working knowledge of NLU concepts: intents, entities, utterances, and conversational design best practices.
• Proficiency in Jira for task tracking and Git for version control.
• Strong analytical and debugging skills — able to diagnose complex technical issues and optimise application performance.
• Ability to work independently on assigned features with minimal supervision.

Nice to have:

• Experience deploying conversational AI for enterprise clients in banking, insurance, or utilities.
• Familiarity with CCaaS platform integrations (e.g., Genesys, Avaya, NICE).
• Exposure to CI/CD pipelines and automated testing frameworks.
• Understanding of voice biometrics and speech recognition systems.

The Software Engineer (Conversational AI Application Developer), Mid develops, implements, and maintains high-quality conversational AI applications on the Omilia Cloud Platform (OCP). Compared with Junior, Mid carries more ownership of customer requirements gathering, application design, and internal mentoring / task coordination as experience grows — and is expected to gain confidence in Omilia’s stack faster when hired at Mid. The role ensures seamless user experiences and robust technical performance across enterprise client deployments, working within a squad under a Team Lead or Solution Delivery Manager.

Accountabilities

• Feature Ownership: Accountable for the end-to-end development and unit testing of specific conversational features and miniApps.
• Technical Execution: Ownership of the implementation of business logic and conversational flows as defined in Detailed Design Specifications (DDS).
• NLU Management: Accountable for the creation, uploading, and basic tuning of NLU models and resources.
• System Stability: Ownership of troubleshooting and resolving defects identified during QA, UAT, or production hypercare phases.
• Environment Management: Accountable for the successful deployment and promotion of applications across OCP environments (Dev, UAT, Prod).

Key Responsibilities

• Write clean, maintainable code to build conversational dialogs, integrating with backend web services and CCaaS platforms.
• Prepare and upload NLU training data, manage intent selection policies, and ensure high concept identification success rates.
• Perform rigorous unit testing and use tools like ELK/Kibana to analyse logs and resolve runtime errors.
• Maintain technical documentation for implemented features and contribute to master prompt lists and implementation steps.
• Participate in daily stand-ups and sprint planning, providing accurate task estimates and surfacing technical risks early.
• Manage application deployments and promotions across OCP environments, following Omilia's change management protocols.

The Software Engineer (Conversational AI Application Developer), Mid develops, implements, and maintains high-quality conversational AI applications on the Omilia Cloud Platform (OCP). Compared with Junior, Mid carries more ownership of customer requir...

Required:

• Strong hands-on experience with the Omilia Cloud Platform (OCP) and its core components — Dialog Manager, NLU, miniApps, or hands-on experience in production-grade development with other Conversational AI Platforms.
• Solid background in software development, including JavaScript/Node.js and working with RESTful APIs and JSON.
• Working knowledge of NLU concepts: intents, entities, utterances, and conversational design best practices.
• Proficiency in Jira for task tracking and Git for version control.
• Strong analytical and debugging skills — able to diagnose complex technical issues and optimise application performance.
• Ability to work independently on assigned features with minimal supervision.

Nice to have:

• Experience deploying conversational AI for enterprise clients in banking, insurance, or utilities.
• Familiarity with CCaaS platform integrations (e.g., Genesys, Avaya, NICE).
• Exposure to CI/CD pipelines and automated testing frameworks.
• Understanding of voice biometrics and speech recognition systems.