Principal Solutions Architect, Generative AI, AWS Industries, Telco

About the role

The Principal Solutions Architect, Generative AI, will accelerate AI adoption across North America's largest telecommunications operators. This role bridges the gap between frontier AI capabilities and real-world telco environments, from voice infrastructure to subscriber platforms and network operations centers.

Responsibilities

• Design and deliver generative AI solutions for telco customers across multiple domains: agentic voice, AI assistants, real-time translation, and network operations AI.
• Arcitect end-to-end AI pipelines integrating foundation models, speech, vision, and tool-use agents with telco platforms and infrastructure.
• Build production-quality proof-of-concepts demonstrating agentic capabilities including multi-turn reasoning, tool use, RAG, and real-time voice interaction.
• Lead technical engagements with telco engineering teams on foundation model selection, fine-tuning, prompt engineering, guardrails, and responsible AI.
• Provide strategic guidance on deploying AI agents into telco environments, addressing latency, reliability, compliance, and scale requirements.
• Develop reference architectures and reusable blueprints that accelerate GenAI adoption, combining Bedrock, Transcribe, Polly, Connect, and partner ecosystem components.
• Influence AWS AI service roadmaps by capturing customer requirements and collaborating with service teams.
• Author whitepapers, blog posts, and reference implementations establishing AWS's point of view on GenAI for telecommunications.
• Drive customer growth through GenAI-focused sales strategies in partnership with AWS Sales teams.
• Build trusted advisor relationships with senior technical leaders (VP Eng, CTO, Chief AI Officer) at telco customers.

Qualifications

• 10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• Experience communicating across technical and non-technical audiences and at C-level, including training, workshops, publications
• Experience developing technology solutions and evangelising end-to-end technology roadmaps that guide IT transformations toward cloud computing
• Experience building complex software systems that have been successfully delivered to customers, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
• Experience designing, building, operating, and managing large-scale distributed systems or web services