Senior AI Architect & Lead Prompt Engineer
Location: Sunnyvale, CA
Contract
Role Overview
The Senior AI Architect & Lead Prompt Engineer will spearhead the design and deployment of advanced, next-generation agentic systems and LLM-powered platforms for GFiber.
This pivotal role necessitates the integration of sophisticated Prompt Engineering and AI Architecture principles with scalable AI infrastructure to optimize GFiber's enterprise workflows.
Leveraging a background in the Telecommunications sector, the incumbent will integrate AI agents with core enterprise platforms, including but not limited to ServiceNow, Salesforce, Netcracker, and SAP, to automate complex customer inquiry cycles and enhance on-field employee support. This integration is designed to yield substantial reductions in Capex and Opex, ensure end-to-end service management for both internal and external GFiber stakeholders, and involve the creation of reusable AI assets and the cultivation of mentorship capabilities.
Key Responsibilities
AI Architecture & Design: Lead the end-to-end architecture of multi-agent systems, moving from initial concept to production-grade deployment on Google Cloud Platform (Google Cloud Platform).
Prompt Engineering & Orchestration: Develop sophisticated prompt engineering frameworks, including system prompts, few-shot templates, and output guardrails. Utilize Chain-of-Thought (CoT) prompting and structured prompt chains for complex reasoning tasks.
Intelligent Dialog Systems: Design conversational interfaces using Dialogflow and Gemini-powered agents to manage inquiry routing and automated workflow orchestration.
System Integration: Architect integrations between LLM platforms (Vertex AI/Gemini) and enterprise CRM/ITSM tools like Salesforce and ServiceNow, specifically focusing on Telecom-grade inquiry response and ticketing workflows.
RAG & Knowledge Retrieval: Build and optimize RAG (Retrieval-Augmented Generation) pipelines grounded in internal client policies and technical documentation.
MLOps & Deployment: Oversee the deployment of microservices using GKE (Google Kubernetes Engine), Cloud SQL, and Cloud Build, ensuring scalable and reliable AI performance.
Required Core Expertise
LLM Stack: Deep expertise in Gemini, Vertex AI, and LangChain or LlamaIndex.
Enterprise Integration: Proven experience architecting AI solutions that interface with Salesforce and ServiceNow within a Telecom or large enterprise context.
Agentic Systems: Experience building multi-agent architectures for autonomous task execution and workflow automation.
Data & Search: Mastery of hybrid search, reranking, and vector databases (e.g., Redis, PostgreSQL).
Qualifications
Experience: 10+ years in the AI stack, ranging from classical NLP/NLU to modern generative AI architectures.
Education: B.Tech in Computer Science, Mathematics, or a related technical field.
Technical Proficiency: Strong command of Python, Terraform IAC, Docker, and the Google Cloud Platform ecosystem (GKE, Cloud Deploy).
Industry Knowledge: Demonstrated understanding of the Service Now, Salesforce, Net Cracker in Telecommunications service lifecycle, specifically regarding inquiry management and automated support.
Tools & Platforms
AI/ML: Gemini, Vertex AI, Hugging Face, OpenAI, Claude.
Frameworks: LangChain, LlamaIndex, Dialogflow.
Cloud & Infra: Google Cloud Platform (GKE, Cloud Build), Docker, TensorRT.
Data: Cloud SQL, PostgreSQL, Redis.
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