Conversational AI Engineer
Foundever Group
Foundever™ At Foundever, we are revolutionizing customer experience (CX) with cutting-edge digital solutions. As we grow, we are building a pioneering Digital Services organization, and we’re looking for exceptional talent to join our Delivery Conversational AI team. The Conversational AI Engineer is responsible for developing and deploying Conversational AI solutions (chatbots and voicebots), using LLMs, Agentic AI, NLU, and RAG technologies. This role executes technical implementations and integrations across environments while translating business and conversational requirements into scalable, secure, and maintainable technical solutions. It is responsible for defining the technical architecture, integration strategy, APIs, authentication, data flows, AI orchestration, and deployment approach, ensuring compliance with enterprise standards and best practices. The role leads technical discovery and feasibility assessments, implementing and integrating Conversational AI platforms with enterprise systems, CRMs, knowledge bases, telephony, backend services, and third-party applications. It combines expertise in solution architecture, prompt engineering, knowledge base structuring, AI orchestration, and system integration to enable end-to-end automation and continuous improvement. The Conversational AI Engineer also ensures safe and reliable AI model behavior through guardrails, testing, proactive monitoring, troubleshooting, fine-tuning and optimization of prompts, retrieval strategies, and AI model configurations. Additionally, the role oversees STT/TTS configuration and maintenance, voice infrastructure, telephony integration, observability, and performance optimization to guarantee high-quality voice experiences and seamless system integration.Job Responsibilities
- Implement, deploy, and maintain Voicebot and Chatbot solutions across development, technical testing/UAT, and production environments
- Perform technical discovery and feasibility assessments by evaluating integrations, APIs, data sources, platform capabilities, architecture constraints, technical dependencies, and implementation requirements
- Define and maintain the technical solution architecture, including integration architecture, APIs, authentication, data flows, AI orchestration, and deployment approaches, ensuring scalability, security, maintainability, and alignment with enterprise standards
- Implement and manage system integrations to enable seamless automation across enterprise platforms, applications, and backend systems
- Ensure safe and reliable AI model by implementing safeguards and governance measures
- Engineer and refine prompts to guide LLM behavior and ensure precise, context-aware, and business-aligned responses
- Structure and optimize knowledge bases to ensure accurate and context-aware responses
- Select, configure, integrate, and optimize the most suitable STT and TTS technologies for each use case and language, considering accuracy, latency, voice quality, cost, and platform compatibility to ensure reliable voice performance
- Implement and support telephony integrations for voicebot solutions
- Apply technical best practices and recommendations for LLMs, Agentic AI, and hybrid AI solutions (NLU + LLM)
- Implement new integrations and backend components required to support Conversational AI solutions
- Document solution architectures, technical specifications, configurations, integrations, and deployment processes to ensure maintainability and knowledge sharing; Detect and mitigate technical risks and issues
- Identify and mitigate technical risks, issues, and dependencies throughout the project lifecycle
- Define technical standards, implementation guidelines, and reusable architecture patterns to ensure consistency, scalability, and maintainability across Conversational AI solutions
- Collaborate with Conversational Designers, Delivery Managers, Data Analysts, business stakeholders, and cross-functional teams to deliver scalable and business-aligned Conversational AI solutionsSkills and Qualifications
- Knowledge of Conversational AI, including RAG, LLMs and NLU
- Degree or background in engineering or development
- Experience working with Conversational AI platforms and deploying AI bots
- Experience with speech technologies, including STT (speech-to-text) and TTS (text-to-speech)
- Experience in deployment and integration, including APIs and system integrations
- Experience with prompt engineering
- Ability to clearly document architectures, configurations, and deployment procedures
- Fluent in written and spoken English
- Python / JavaScript / Typescript, Very important, since Cognigy uses JS/TS for scripting, validations, data transformations, and flow logic. and Python for all the AI part
- JSON or YAML Used to configure nodes, inputs, outputs, and API payloads
- SQL / NoSQL queries For accessing databases when the bot needs external information
- API Integration: RESTful APIs, Webhooks, OAuth authenticationAbout Us
- LI-Remote
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