Summary
✨ AI‑Generated
A lead software engineer is sought to architect and build sophisticated generative AI agents and modern conversational systems. The role includes migrating legacy interfaces to AI-driven architectures, integrating enterprise communication and CRM systems through APIs and middleware, and improving agent capabilities through prompt engineering, grounding, reasoning, and tool use. The position offers substantial exposure to enterprise AI transformation.
Highlights
Lead-level opportunity focused on generative AI agents, conversational AI modernization, enterprise integrations, prompt engineering, and cloud platform transformation.
Description
EMEA Cloud Platform & Infra Engineer - GECX
Key Responsibilities
Agent Development: Architect and build sophisticated AI agents using Gemini Enterprise for
Customer Experience, Gemini models and CXAS, focusing on reasoning, grounding, and
tool-use capabilities.
Platform Migrations: Migration of legacy conversational interfaces (e.g., Dialogflow Cx,
Playbooks, or third-party bots) to advanced CXAS and generative AI architectures.
Agent Assist & Conversational Insights: Design and implement Agent Assist features (e.g.,
Generative Knowledge Assist, Proactive GKA, AI Coach, Live Translation) and utilize CCAI
Insights to analyze conversations and drive continuous improvement.
Telephony & System Integration: Connect AI agents to existing CCaaS/telephony platforms
(e.g., Genesys, Cisco, Avaya) and enterprise CRM infrastructure (e.g., Salesforce, Zendesk)
using APIs and middleware to ensure real-time data access and seamless omnichannel routing.
Prompt Engineering & Tuning: Develop and optimize complex prompts and orchestration
layers to ensure high accuracy, brand voice consistency, and safety.
RAG Implementation: Design and maintain Retrieval-Augmented Generation (RAG) pipelines
to provide agents with up-to-date, grounded knowledge from company documentation and
knowledge bases.
Infrastructure & CI/CD: Manage CI/CD pipelines and DevOps automation for agent
development using tools like Terraform to ensure scalable, infrastructure-as-code deployments.
Agent Ops & Performance Monitoring: Establish robust Agent Ops practices, implementing
evaluation frameworks to measure agent latency, accuracy, safety, and customer satisfaction,
and iterating based on data-driven insights.
Collaboration: Work closely with CX leads and product managers to translate business
requirements into technical AI workflows.
Qualifications
Minimum qualifications
Bachelor’s degree in Computer Science, Engineering, a related technical field, or
equivalent practical experience.
7 years of experience in technical client services.
Experience in the design and/or implementation of Cloud based technical architectures
and solutions.
LLM & GECX Proficiency: Deep understanding of Large Language Models.
