Cloud Platform & Infrastructure Engineer — GECX / Conversational AI
BE Shaping The Future- Location
- Location not stated
- Workplace
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- Employment
- Full Time
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Posted 12d ago
Cloud Platform & Infrastructure Engineer — GECX / Conversational AI - BE Shaping The Future | Career Page
Cloud Platform & Infrastructure Engineer — GECX / Conversational AI
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Job Openings Cloud Platform & Infrastructure Engineer — GECX / Conversational AI
About the job Cloud Platform & Infrastructure Engineer — GECX / Conversational AI
Core Requirement
Engineers with strong Python and Conversational AI expertise are required. Experience with Dialogflow is highly preferred. Key skills include Google Cloud Platform (GCP), Dialogflow, Large Language Models (LLMs), Gemini Enterprise for Customer Experience (GECX), agent development, Agent Assist, Conversational Insights, telephony and enterprise system integrations, API development, and backend engineering.
Responsibilities
Agent Development
- Architect and build sophisticated AI agents using Gemini Enterprise for Customer Experience, Gemini models, and CXAS.
- Design and implement advanced reasoning, grounding, and tool-use capabilities.
Platform Migrations
- Migrate legacy conversational interfaces, including Dialogflow CX, Playbooks, and third-party bots, to CXAS and generative AI architectures.
Agent Assist & Conversational Insights
- Implement Agent Assist capabilities, including:
- Generative Knowledge Assist (GKA)
- Proactive GKA
- AI Coach
- Live Translation
- Utilize CCAI Insights for conversation analysis and operational improvements.
Telephony & System Integration
- Integrate AI agents with CCaaS and telephony platforms, including:
- Genesys
- Cisco
- Avaya
- Connect conversational solutions with enterprise CRM platforms, including:
- Salesforce
- Zendesk
- Develop API and middleware integrations to support real-time omnichannel routing.
Prompt Engineering & Tuning
- Design and optimize complex prompts and orchestration layers.
- Ensure response accuracy, brand voice consistency, and safety controls.
Retrieval-Augmented Generation (RAG)
- Build and maintain Retrieval-Augmented Generation pipelines leveraging enterprise documentation and knowledge bases.
Infrastructure & CI/CD
- Develop CI/CD pipelines and DevOps automation using Terraform.
- Implement scalable infrastructure-as-code deployment models.
Agent Operations & Monitoring
- Establish evaluation frameworks for latency, accuracy, quality, and safety.
- Monitor and optimize agent performance across production environments.
Collaboration
- Partner with CX Leads and Product Managers to translate business requirements into conversational AI solutions.
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Or refer someone
Share
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- X (Formerly Twitter)
Skills
- Python
- Dialogflow
- Google Cloud Platform
- GCP
- Large Language Models
- LLMs
- Gemini Enterprise for Customer Experience
- GECX
- Gemini
- CXAS
- Dialogflow CX
- Playbooks
- Agent Assist
- Generative Knowledge Assist
- GKA
- AI Coach
- Live Translation
- CCAI Insights
- Genesys
- Cisco
- Avaya
- Salesforce
- Zendesk
- Terraform
- RAG
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