Senior AI Architect

Role: Senior AI Architect

Location: Sunnyvale, VA(Local candidates preferred) Onsite

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.