Back
Tier-1 brand plus metro location but senior, specialized conversational AI reduces applicant density.
Conversational AI skills transferable to other sectors, but Dialogflow/GCP and healthcare preference increases domain specificity.
Several explicit years and mandatory Dialogflow, GCP, and Python experience impose strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design, deployment, and optimization of enterprise-scale conversational AI platforms using Google Dialogflow CX and Google Agent Development Kit (ADK).
Develop and fine-tune NLP/NLU models for high accuracy in intent classification and dialogue management in voice bots and IVR systems.
Collaborate with cloud architects and product owners to implement secure, scalable conversational workflows and microservices on Google Cloud Platform with CI/CD automation.
Bachelor's degree (BE/BTech) in Computer Science, Engineering, or related technical field, or 12+ years of equivalent software/AI engineering experience.
10+ years of professional software engineering experience focused on AI/ML, NLP/NLU, or Conversational AI.
8+ years of Python 3.x production-grade coding experience.
3+ years hands-on experience designing, developing, deploying conversational agents using Google Dialogflow CX; 1+ years with Google ADK; 5+ years building cloud-native solutions on GCP or major public cloud; 5+ years utilizing Git/GitHub and automated CI/CD for AI/ML.
Experienced in architecting and scaling complex voice bot or IVR conversational AI systems in enterprise environments using Google Cloud-native tools.
Ability to lead engineering teams, establish technical best practices, and communicate architecture to senior leadership.
Strong background integrating AI/ML conversational solutions with cloud microservices, enterprise-grade contact center platforms, and real-time API event-driven architectures.