Senior Worldwide (WW) GTM Specialist, Amazon WorkSpaces

AI in this role

bedrock

ai-agents

The workspace is no longer just for humans. Enterprises are moving from traditional virtual desktops to intelligent, cloud-native environments where people and AI agents work side by side — governed by design, observable by default, and delivered anywhere. Amazon WorkSpaces is leading this transformation with WorkSpaces for Agents (now generally available), alongside WorkSpaces Personal, WorkSpaces Core, and WorkSpaces Applications. Together with services like AWS Context and Amazon Bedrock AgentCore, we're building the operating environment for the next enterprise workforce — one where AI agents navigate applications, automate workflows, and build institutional knowledge inside trusted boundaries. The companies that lead won't just have the smartest AI — they'll build the most trustworthy place for intelligence to work.

AWS is seeking a Worldwide (WW) GTM Specialist to accelerate adoption of Amazon WorkSpaces' AI and agentic capabilities. You will be part of a dedicated team focused on bringing these emerging solutions to market — defining the vision for agentic workspaces, building GTM motions around AI-enhanced features, and helping customers understand how governed cloud workspaces become the operating environment for their human + agent workforce. You'll be charting new territory at the intersection of end-user computing and enterprise AI — identifying early adopters, shaping lighthouse engagements, and building repeatable plays that scale.

You are a strategic thinker who operates with urgency. You combine deep business acumen with enough technical depth to be credible with CIOs and IT leaders navigating the shift to agentic work. You understand that the hardest problem isn't teaching an agent to click — it's making sure those clicks happen inside an environment the organization can trust. You've built GTM strategies in emerging technology categories, rallied cross-functional teams around a shared vision, and delivered measurable business results. You're energized by ambiguity — because that's where the biggest opportunities live.

Key job responsibilities
- Define and execute the GTM strategy for Amazon WorkSpaces AI and agentic solutions — identifying high-value customer segments where agents can drive immediate productivity gains, and building programs that accelerate early adoption of WorkSpaces for Agents, AI-enhanced desktop experiences, and governed agentic environments.
- Shape the narrative around the future of agentic workspaces — positioning AWS as the leader in trusted environments where humans and AI agents work together, with built-in governance, observability, and identity management that enable enterprises to scale autonomous work confidently.
- Engage directly with enterprise leaders and partners to articulate how governed cloud workspaces solve the trust, security, and compliance challenges that keep agentic AI stuck in pilots — connecting agentic workspace capabilities to measurable business outcomes.
- Build and scale lighthouse engagements with early adopters deploying AI agents in enterprise environments — generating compelling proof points around agent governance, productivity, and the human + agent operating model, then operationalizing those wins into repeatable plays.
- Develop deep fluency in the WorkSpaces AI portfolio (WorkSpaces for Agents, integration with AWS Context, Amazon Bedrock AgentCore, AWS Continuum) to articulate how the pieces fit together for customers across industries.
- Establish data-driven mechanisms to measure adoption of agentic features, track program effectiveness, and continuously optimize the path from pilot to production-scale agent deployment.
- Evangelize the agentic workspace vision externally through thought leadership, events, and industry engagement — and internally across AWS to drive mindshare and investment in this emerging category.
- Orchestrate field uptake of AI-focused sales plays, equipping the broader sales organization to identify and qualify agentic workspace opportunities and deliver value through repeatable mechanisms.

Basic qualifications

- 5+ years of Go-To-Market, Business Development, Sales, or Consulting experience
- 2+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- 5+ years of working with Business Application Technologies, including, but not limited to End User Compute (EUC), Supply Chain, Contact Center as a Service, Consumer Data Applications, Encrypted Communications, and/or Communication Developer Services experience
- Experience selling enterprise software or cloud-based applications

Preferred qualifications

- Experience interpreting data and making business recommendations across leadership and cross-functional teams
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience in selling nascent products/services into new markets
- Experience leading complex, multi-year initiatives that may be cross-functional and/or span business and technology
- Understanding of enterprise desktop/workspace environments and the security, compliance, and identity requirements that govern them

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Senior Worldwide (WW) GTM Specialist, Amazon WorkSpaces at Amazon rates 77 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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