Sr. Google CCAI Engineer

Diversity Inc
New York, NY, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Microsoft Azure VoIP Cloud Engineering Data Stores Identity and Access Management Python (Programming Language) Redis OpenAI Search Technologies Data Logging
+13 more
Google Cloud Genesys Retrieval-Augmented Generation Large Language Models Grafana Prompt Engineering HybridCloud Backend Kubernetes Stream Processing Serverless Computing Docker Microservices

Job description

We 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., Maintain 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 platforms Define reference architectures for GenAI components (LLMs, vector stores, APIs, orchestration layers)

Requirements

Core Focus (Must-Have)Hands-on experience with Google Cloud Platform, especially Contact Center AI (CCAI), Agent Assist, DialogflowPub/Sub, Cloud Run, IAM, service accounts Experience building or supporting real-time / streaming systems Strong backend development skills (Python)Docker and cloud-native microservices Generative AI / ML (Required)Experience delivering LLM-based solutions in production Familiarity with RAG architectures, vector search, and evaluation Prompt engineering and response quality tuning Understanding of responsible AI, privacy, and security considerations Nice to Have Telephony or contact-center platforms (SIPREC, Genesys, VoIP)Redis or other low-latency data stores Kubernetes / HelmAzure services (AKS, Azure OpenAI) in hybrid cloud setups Observability tools (logging, metrics, tracing)

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