Sr. Solutions Architect - Applied AI for Emerging Products, AWS Applied AI Solutions

About the role

This position is part of the AWS Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains, providing the business and technical expertise to help our customers succeed. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together they provide our customers with the expertise and scale needed to build innovative solutions for their most complex challenges.

As a Specialist Solutions Architect, you will work at the intersection of AI, simulation, and real-world autonomous systems. You will own the technical relationship with design-partner customers — serving as their primary architectural guide from early engagement through production, managing delivery cadences, architecture syncs, and product issue prioritization. You will be both the voice of the customer to internal product teams and a hands-on practitioner who builds demos, validates releases, and enables implementations.

Externally, you will author blog posts, reference architectures, and perspective documents that establish AWS's point of view in the ADAS, autonomous vehicle, and physical AI domains. Internally, you will drive field enablement — creating artifacts, tools, and training content that empower the broader SA community to position and deliver autonomous operations solutions.

Key responsibilities

• Customer Architecture & Delivery Ownership: Serve as the primary Solutions Architect for key customer engagements — own weekly delivery plans, architecture syncs, and the end-to-end technical relationship from proof-of-concept through production
• Product Quality & Launch Readiness: Rigorously validate product releases across development stages (preview, beta, GA), proactively identifying blockers, filing issues, and building/restoring demo environments to maintain customer confidence through launch milestones
• Technical Unblocking & Escalation: Drive resolution of complex technical issues across identity, data integration, and platform layers — escalate and track blockers to ensure no customer disengages due to product gaps or environment issues
• Domain Solution Design: Design and validate reference architectures for applying AI to ADAS validation, autonomous vehicle development, scenario analysis, and industrial physical AI workloads
• Field Enablement & Tooling: Build enablement assets (agents, guides, sandbox configurations) that scale the team's ability to demonstrate value and onboard new customers rapidly
• Thought Leadership & GTM Content: Author blog posts, GTM perspective documents, and customer-facing narratives that articulate AWS's differentiated approach to autonomous operations
• Cross-Functional Collaboration: Work across product management, engineering, business development, and customer success teams to shape product roadmap priorities informed by direct customer feedback
• Customer Expansion: Identify and cultivate new customer opportunities across adjacent verticals (robotics, industrial IoT, smart infrastructure) that benefit from autonomous operations capabilities

About the team

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Basic qualifications

• 8+ years of specific technology domain areas (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• 10+ years of IT development or implementation/consulting in the software or Internet industries experience

Preferred qualifications

• Experience in customer-facing product development and product management, including defining, launching, and optimizing product and services
• Experience building launch readiness frameworks, standard work, playbooks, and scalable deployment mechanisms across multiple concurrent sites, or experience communicating technical concepts to non-technical audiences
• Demonstrated ability to maintain customer engagement and confidence through ambiguity, timeline shifts, and product maturity challenges
• 3+ years of experience in the autonomous vehicles, ADAS, robotics, or physical AI domain — including familiarity with simulation frameworks, scenario-based testing, sensor data pipelines, or perception/planning stacks
• Hands-on experience building demo environments, validating product releases, and translating product gaps into actionable engineering requirements
• Experience with IoT platforms, digital twins, or data-intensive AI/ML workloads in industrial or automotive settings