Senior CCAI/GenAI Solutions Engineer- 7+ yrs- New York, United States- Onsite
Why This Role Stands Out
Advance your career with a leading firm by architecting and implementing cutting-edge Generative AI solutions for contact centers, leveraging your expertise in Google CCAI and cloud-native development. This hybrid role offers a fantastic opportunity to shape the future of AI in customer interactions and is perfect for a driven engineer with a passion for innovation and impactful technology. Join a dynamic team and contribute to groundbreaking projects that will define the next generation of AI-powered services.
Quick Overview
Job Description
Job Requirements JD: Sr. Google CCAI EngineerRole SummaryWe are seeking a Senior AI / Cloud Engineer to implement and extend Real-Time Call Listening and Agent Assist platform built using Google Contact Center AI (CCAI).The role also involves contributing to broader AI and Generative AI solution architecture, including the design and evolution of event-driven, cloud-native services that leverage enterprise-approved LLMs to deliver real-time insights, guidance, and automation across contact center and agent-facing applications.Key ResponsibilitiesMaintain and evolve event-driven contact center services built on CCAI and Google Cloud Platform that process real-time customer interactions and deliver contextual insights, recommendations, or guidance to agent-facing applications during live engagements.Design and implement GenAI solution architectures using enterprise-approved LLMs and cloud platformsDefine reference architectures for GenAI components (LLMs, vector stores, APIs, orchestration layers)Required Skills & ExperienceCore Focus (Must-Have)Hands-on experience with Google Cloud Platform, especially:Contact Center AI (CCAI), Agent Assist, DialogflowPub/Sub, Cloud Run, IAM, service accountsExperience building or supporting real-time / streaming systemsStrong backend development skills (Python)Docker and cloud-native microservicesGenerative AI / ML (Required)Experience delivering LLM-based solutions in productionFamiliarity with RAG architectures, vector search, and evaluationPrompt engineering and response quality tuningUnderstanding of responsible AI, privacy, and security considerationsNice to HaveTelephony or contact-center platforms (SIPREC, Genesys, VoIP)Redis or other low-latency data storesKubernetes / HelmAzure services (AKS, Azure OpenAI) in hybrid cloud setupsObservability tools (logging, metrics, tracing)Work Experience 7-10Years
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