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We are looking for a Senior Conversational AI Engineer with strong hands-on experience building and supporting enterprise conversational and voice AI solutions using Google Dialogflow CX and the Google CCAI / Customer Engagement ecosystem. This is a hands-on engineering role for someone who has worked on real enterprise contact-center implementations that have gone into production, not only POCs or chatbot prototypes. You will help modernize traditional IVR and contact-center experiences into intelligent voice and conversational AI solutions using Dialogflow CX, Google Customer Engagement/CX capabilities, Gemini, Vertex AI and RAG. The ideal candidate has recently designed and developed conversational solutions, understands how the conversational layer integrates with telephony/contact-center platforms and enterprise backend systems, and has experience supporting solutions in production at enterprise scale. Designation: Senior Conversational AI Engineer Location: Remote Work Employment Type: Full Time What You Will Do: Design and develop enterprise voice and conversational AI solutions using Dialogflow CX and Google CCAI / Customer Engagement technologies.Build complex Dialogflow CX implementations covering flows, pages, intents, entities, routes, parameters, session handling, fulfillment, fallbacks and multi-turn conversations.Modernize traditional IVR/contact-center journeys into AI-powered voice and conversational experiences.Design conversational journeys for use cases such as customer service, self-service, transactional workflows and human-agent escalation.Integrate Dialogflow/Google conversational solutions with contact-center and telephony platforms such as Genesys, NICE CXone, Cisco or similar enterprise platforms.Implement live-agent handoff, context/session transfer and escalation between virtual agents and human agents.Integrate conversational solutions with enterprise systems through REST APIs, webhooks and fulfillment services using Python and/or Node.js.Work with STT/TTS and enterprise voice integrations for production voice-bot implementations.Use Gemini, Vertex AI and Google generative conversational capabilities to enhance customer interactions.Design and implement RAG/enterprise knowledge retrieval patterns to provide grounded responses and reduce hallucinations.Apply appropriate deterministic vs. generative conversational patterns based on the business use case, risk and customer experience.Troubleshoot production issues across conversational flows, integrations, APIs, voice/telephony and LLM-based components.Participate directly in client discovery and translate business/contact-center requirements into practical conversational solution designs.Work with architects, backend engineers, cloud/data teams and client stakeholders from design through production implementation and support. Must-Have Experience: 3+ years of hands-on Conversational AI / Voice AI experience, with recent experience in the Google ecosystem strongly preferred.Strong hands-on development experience with Dialogflow CX.Experience working on at least one enterprise Conversational AI / CCAI solution that has gone into production.Experience building voice bots and/or contact-center conversational solutions, not only web chatbots.Strong understanding of Dialogflow CX architecture, including intents, entities, flows, pages, routes, parameters, fulfillment, session management, fallbacks and multi-turn conversations.Experience integrating conversational AI with a contact-center/telephony platform such as Genesys, NICE CXone, Cisco or equivalent.Experience with human-agent handoff and conversation/context transfer.Hands-on API/webhook/fulfillment integration experience using Python and/or Node.js.Understanding of STT/TTS and voice AI architecture.Experience with Gemini, Vertex AI, CX Agent Studio/Google Customer Engagement capabilities, Playbooks or similar Google generative conversational technologies.Practical understanding of RAG, grounding, enterprise knowledge retrieval and hallucination reduction.Experience working with enterprise customers and translating business requirements into conversational flows and technical approaches.Experience troubleshooting and supporting production conversational AI applications. Strongly Preferred: Experience with 2+ enterprise Dialogflow CX / Google CCAI implementations.Experience supporting high-volume production conversational platforms.Experience modernizing legacy IVR - Dialogflow CX / AI-powered voice experiences.Recent experience with CX Agent Studio / Google Customer Engagement / Gemini-based conversational solutions.Experience with Agent Assist or human-agent augmentation.Exposure to Agentic AI, tool/function calling and multi-step agent workflows.Google Cloud experience across services commonly integrated with conversational AI solutions. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.