Software Development Manager, ICON
Amazon is hiring a Software Development Manager, ICON in Dublin, Ireland. Level rates it ; you can apply on Amazon.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- The posting mentions AI agents among its tools and skills.
- Amazon has 22,000+ other open roles on Level.
- Posted in the last few days.
AI in this role
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 production, and prove its value through measurable results in hours saved and execution success.
A day in the life
As the Dublin SDM, you balance engineering execution, technical judgment, and people leadership. A typical week might look like this:
• Reviewing a design for a new test pipeline stage that applies lessons from a recent operational event, so every generated workflow is checked against that failure mode.
• Meeting with a partner team about a repetitive operational task, and leaving with a plan to turn it into the next automated workflow.
• Aligning with partner teams on a shared platform capability your engineers are contributing.
• Pairing with a scientist on your team on how to score workflow quality automatically, so the platform improves with every run.
• Coaching an engineer through their first design review, helping them reason about blast radius and rollback for automation that runs in production.
Your team uses AI in its own engineering work, from design and prototyping to testing and deployment.
About the team
Our team builds and operates the AI-native factory that produces automation for Amazon's production infrastructure. The Dublin team owns the factory's test pipeline and workflow delivery, and contributes core factory capabilities. We are an AI-native team that uses AI across every aspect of our work, from workflow design and code generation to validation and operational monitoring. ICON hosts Amazon's customer-facing websites and backend services, centralizing management and automation so developers across Amazon can focus on customer innovation.
If you want to build at the intersection of AI, distributed systems, and operational automation, and build the safeguards that let engineers rely on AI-generated automation in production, we would like to hear from you.
Basic qualifications
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience managing teams, or experience building complex software systems that have been successfully delivered to customers
- Experience designing, building, operating, and managing large-scale distributed systems or web services
- Track record of partnering with product, program, and technical leadership to define strategy and priorities
Preferred qualifications
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers
- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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
Software Development Manager, ICON at Amazon rates 67 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.
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. Read the description and count the AI tools, models and workflows it names.
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Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
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- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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