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AWS Specialist Technology Team (STT) is seeking a Software Development Manager to lead the Specialist AI Tooling engineering team - the group building AI-native, agentic solutions that are fundamentally transforming how thousands of AWS technical specialists and field team members develop expertise, get matched to customer engagements, and how AWS service teams consume customer feedback at scale. 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 four interconnected products that collectively power the intelligence layer of AWS's specialist ecosystem:
- AWS Learning Agent - A new generative AI-powered, agentic learning system that replaces static training paths with personalized, cross-domain skill development for every builder in the AWS technical field. Powered by a structured skill graph, persistent learner profiles, and the Specialist Knowledge Vault, the Learning Agent delivers adaptive learning journeys via a custom console, in Kiro, Claude, Quick and wherever builders work.
- Intelligent Routing Agent - A new AI-driven routing engine that matches 136K+ annual specialist requests to verified domain experts using validated skill profiles rather than manually maintained lists - reducing resolution time (currently 7.72 days) and enabling precision matching at scale.
- Technical Field Community (TFC) Hub - The platform powering 46 Technical Field Communities, managing member engagement, competency tracking, learning path orchestration, and community-driven content curation across AWS's specialist network

- Service 360 - A GenAI summarization and prioritization engine that aggregates customer feedback signals (PFRs, SpecReqs, SFDC Opportunity data) into categorized, prioritized service recommendations - automating what was previously a manual closed-loop feedback process to influence the roadmap for AWS public service teams.
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 graphs, multi-agent orchestration, LLM-powered personalization, and retrieval-augmented generation - all at AWS scale, using the very AI services AWS builds for its customers.
Key job responsibilities
- Lead the engineering team building AI-native products that power AWS's specialist ecosystem - including an agentic learning system, intelligent routing agent, the Technical Field Community Hub platform, and a GenAI-powered customer feedback engine (Service 360).
- Architect and ship production agentic AI systems using LLMs, knowledge graphs, RAG, and multi-agent orchestration - delivering personalized learning paths and intelligent expert-matching to thousands of field members daily.
- 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 evolution of intelligent routing algorithms that match 136K+ annual specialist requests to verified domain experts using AI-validated skill profiles and demand signals.
- Design and operate GenAI summarization pipelines that transform thousands of customer feedback signals into prioritized, actionable service recommendations for AWS service leadership.
- Own the technical strategy and roadmap across all four products, making trade-offs between speed-to-delivery and long-term platform scalability.
- Partner with Product, Science, 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 field teams operate. The pace of innovation is high, the problems are ambiguous, and the impact is measured across thousands of field team members and the customers they serve. This role offers the opportunity to define a function from the ground up and shape how an entire organization consumes and acts on data.
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