AWS Specialist Technology Team (STT) is seeking a Software Development Manager to lead the Specialist GTM AI Tooling engineering team, the group building AI-native, agentic solutions that are fundamentally transforming how AWS Go-To-Market (GTM) teams turn customer opportunities into sales plays, and how those plays reach thousands of AWS field team members in the tools where they already work. If you want to build production agentic AI systems that impact thousands of users daily (not research prototypes, but real AI agents solving real problems), this is the role for you.
You will own and grow a team of Software Development Engineers responsible for building brand new and enhancing existing products that collectively connect AWS's go-to-market strategy to field execution:
- Specialist Knowledge Vault (SKV) - An AI-first knowledge service that uses purpose-built crawlers to index specialist content from a wide range of sources, which removes manual consolidation. SKV lets Technical Field Communities (TFCs) endorse golden content, add agent steering, build reusable playbooks, and flag outdated or incorrect content. SKV powers the AWS Specialist Agent, which more than 11,000 field team members used across nearly 100,000 conversations in its first three months.
- SKV Playbooks for GTM - Your team will own playbooks in SKV and extend them to natively represent GTM sales plays, including positioning guidance for every stage of the sales funnel, so AI agents deliver the right play to sellers with endorsed content and clear provenance. You will build the capabilities that let domain and industry leaders author with AI assistance, draft and test changes before they go live, detect duplicate or conflicting plays, and score playbook health, then migrate AWS's service-aligned GTM domains onto the platform.
- SKV Recommendations Engine - Your team will own the closed-loop AI/ML recommendation service that analyzes agent conversations, telemetry, and customer feedback signals to tell content owners what to fix next: knowledge gaps where the agent had no good answer, and inaccurate or outdated content it should no longer trust. Recommendations become next-best actions, such as updating a playbook, refreshing a first call deck, or creating new solution guidance, which agents can draft automatically for human review.
- Alchemy - The platform where AWS GTM teams capture and prioritize customer use cases and map first-party and third-party solutions to them. Alchemy's taxonomy, data products, and MCP server, which now reaches more than three times as many users as its web interface, provide the structured GTM foundation and downstream integrations that the SKV experience builds on.
This is a high-impact, AI-first leadership role where you will architect agentic systems, ship production GenAI features, and lead a team solving problems at the intersection of knowledge management, agentic authoring, multi-agent orchestration, retrieval-augmented generation, and closed-loop measurement, all at AWS scale, using the very AI services AWS builds for its customers.
Key job responsibilities
- Lead the engineering team that owns GTM playbooks and the recommendations engine within the Specialist Knowledge Vault, along with the Alchemy platform and its integrations.
- Architect and ship production agentic AI systems using LLMs, RAG, MCP, and multi-agent orchestration, delivering endorsed sales plays, assets, and next-best actions to field teams in the tools where they already work.
- Build, manage, and develop a high-performing SDE team, maintaining Amazon's hiring bar while fostering a culture of technical ownership, rapid experimentation, and operational excellence.
- Drive the move of GTM authoring from hand-maintained sales plays to agent-assisted playbooks in KV, with versioning, pre-publish testing, conflict detection, and health scoring that give field teams confidence in AI output.
- Evolve the recommendations engine from identifying knowledge gaps and inaccurate content to recommending and drafting the next best action, using signals such as agent conversations, field adoption, pipeline, and customer feedback.
- Own the technical strategy and roadmap across all products, making trade-offs between speed-to-delivery and long-term platform scalability, in close partnership with the engineering teams that share the KV platform.
- Partner with Product, Science, GTM, TFC, and field leadership to translate ambiguous problems into engineering deliverables, and represent the team in executive reviews with Directors and VPs.
About the team
You will be joining a high-growth engineering organization that is at the forefront of applying generative AI and agentic technologies to transform how AWS GTM teams plan, author, and deliver strategy to the field. The pace of innovation is high, the problems are ambiguous, and the impact is measured by how quickly customer opportunities become sales plays in the hands of thousands of field team members and the pipeline they create. This role offers the opportunity to shape how an entire organization builds, governs, and measures AWS' go-to-market content.
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