Senior Specialist Solutions Architect, Bedrock, WWSO Startups

Overview

In this role you help startups adopt AWS Bedrock to run AI-powered inference at scale, acting as a technical advisor and architect. You will engage with startup executives, shape adoption strategies, and deliver scalable Bedrock architectures across industries. The position blends hands-on design with enablement and collaboration across AWS teams to influence product direction. This is a high-impact, customer-obsessed role that drives growth by turning cutting-edge AI capabilities into practical startup outcomes.

Responsibilities

• Engage startup customers from CXO/VP level to drive Bedrock inference adoption and secure lighthouse customers
• Be the go-to expert on foundation models and evaluation techniques to guide startups
• Serve as a trusted advisor on AI-powered applications and architecture
• Design and deploy scalable Bedrock architectures for multiple use-cases and verticals
• Develop programs leveraging AWS Field Solution Architect teams, inference SMEs, model providers, and partners to scale adoption
• Collaborate with AWS service and engineering teams to surface feedback and influence roadmaps
• Create field enablement assets, demo content, and workshop material for the Specialist Architect population

Key requirements

• Bachelor’s degree in computer science, engineering, mathematics or equivalent; or relevant experience
• Experience in a customer-facing role engaging with executives to solve business problems with advanced technologies
• Experience with AI/ML technologies and ML/LLM fundamentals
• Startup background with experience at VC/PE-backed firms in a Technical Executive capacity

• strong storytelling and communication for executive audiences
• stakeholder management and collaboration
• technical thought leadership in AI
• AI/ML technologies and LLM fundamentals including architecture, training/inference lifecycles, optimization
• Foundation models, open-weight and frontier models, world models, agentic frameworks
• Agentic AI architectures; multi-agent orchestration, tool-use patterns, MCP (Model Context Protocol)

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