# Software Development Manager, ICON at Amazon

Amazon is hiring a Software Development Manager, ICON in Dublin, Ireland. Level rates it Works on AI ●●●○; you can [apply on Amazon](https://jobsbylevel.com/go/b80a14c4-3c6a-468d-87c7-727dbedbefe3?utm_medium=ai-agent).

AI Level 3, AI centrality 67 out of 100. IE, D, Dublin.

## Details

- Company: [Amazon](https://jobsbylevel.com/companies/amazon)
- AI level: AI Level 3 (score 67 out of 100)
- Location: IE, D, Dublin
- Posted: October 20, 2026
- Apply: https://jobsbylevel.com/go/b80a14c4-3c6a-468d-87c7-727dbedbefe3?utm_medium=ai-agent

## Prepare for this job

The job page lists 3 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/software-development-manager-icon-at-amazon-e65942

## Description

The Intelligent Cloud Hosting (ICON) team is looking for a Software Development Manager who is passionate to work on the development of innovative software products which will help boost engineers productivity in Amazon, for improving services' posture towards security, availability, efficiency, compliance and maintainability. We aim to eliminate vast quantities of undifferentiated work for Amazon development teams - our opportunity for impact to tens of thousands of developers is enormous. As the Software Development Manager for ICON's team in Dublin, you are a hands-on leader who guides engineers building the AI native factory that produces automation to operate on Amazon's production infrastructure. Your team owns the test pipeline that validates every workflow before it reaches production, builds workflows that run at Amazon scale, and contributes core capabilities to the factory. ICON operates critical services that power the Amazon shopping experience. Keeping those services healthy has required manual runbook authoring, interrupt-driven toil, and undocumented expertise held by individual engineers. The factory replaces that work with validated automation. Engineers describe operational intent in natural language, and the factory produces a validated, production-ready workflow tailored to that service's unique context. An engineer describes a routine change, such as moving a service to a new instance type during the next maintenance window, and the factory generates, validates, and executes the workflow. Engineers state the outcome they need, and the factory supplies the operational knowledge, safety checks, and execution steps. We are an AI-native team. We use AI across every aspect of our work, from workflow generation and validation to execution monitoring and continuous learning. The factory uses AI agents grounded in Amazon's operational history to generate, validate, and improve every workflow it delivers. On this team, AI-native leadership is a daily practice. You use LLMs and agents in your own work, from drafting designs and analyzing operational data to reviewing code and preparing business reviews. You set the standard for how your team builds with AI, measure the productivity gains, and share what works across the organization. You understand how agentic systems behave in production: where they succeed, how they fail, and which guardrails keep them safe. Key job responsibilities – Own the technical vision, roadmap, and architecture for your team's scope, and deliver it end-to-end as the factory takes on new classes of operational work. – Own the test pipeline that every generated workflow passes before production, and use automated evaluation and execution data to measure correctness and catch regressions before release. – Partner with service teams to find high-toil operational tasks and turn them into validated, reusable workflows that run at Amazon scale. – Contribute core capabilities to the factory, and align with partner teams on shared architecture and roadmap. – Expand the share of operational work that agents own end-to-end, moving each workflow in stages from human-approved execution to supervised autonomy. – Make the higher-stakes tradeoffs that come with AI in production: autonomy versus approval, speed versus safety, and model capability versus cost. – Set a safety-first bar for production: separate fast experimentation from production-grade automation, establish operating best practices for traditional and AI-powered workloads, and own risk mitigation and escalations. – Lead your team's adoption of AI development tools, measure the effect on delivery speed and quality, and share proven practices with partner teams. – Hire, retain, and grow a multidisciplinary team of engineers and scientists who ship AI-native products at Amazon scale; set clear goals, give regular feedback, and manage performance. – Earn adoption across service teams by making the factory effortless to use and trustworthy in

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/software-development-manager-icon-at-amazon-e65942

Source: https://jobsbylevel.com/jobs/software-development-manager-icon-at-amazon-e65942

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