Description

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Amazon's global data center infrastructure generates millions of operational alarms daily, and right now most of the triage, analysis, and routing of those alarms requires significant human effort from engineering operations teams. The SKG team within DC BRIDGE is building intelligent systems that fundamentally change how data center engineers interact with alarm data: reducing noise, automating triage, and applying generative AI to surface actionable insights from complex operational signals.

This is a builder role, not a maintainer role. We have a team of 8 engineers (SDE1s and SDE2s) who are talented, motivated, and ready for senior technical leadership. The technical strategy is still being defined. Generative AI hasn't been productionized yet. The opportunity is to be the person who shapes the direction, levels up the team, and gets GenAI into production for real data center operations problems. If you want to walk into a well-oiled machine and keep it running, this isn't the role. If you want to build something from a position of real influence, keep reading.

Our customers are internal: data center operations engineers who work directly with the physical infrastructure. That means tight feedback loops, fast iteration cycles, and the ability to sit down with the people using your systems to understand what's actually working — real Customer Obsession, not the abstract kind.

We want you to walk in with clear eyes. Strategy is still being defined — the team has strong execution capability but needs senior technical leadership to set direction. You won't inherit a roadmap, you'll build one. Input data quality from upstream systems is rough and ripe for optimization. GenAI is unproven here — you'll need to figure out what works and how to get real value from Amazon Bedrock in an operational context, not just build demos.

Tech stack: TypeScript (primary for CDK and service code), Python (data processing, Lambda functions, AI service integration). AWS services include Lambda, DynamoDB, SQS, SNS, S3, CloudWatch, Amazon Bedrock, API Gateway, and Route 53. CI/CD uses Amazon's internal build, test, and deployment tooling including Hydra for integration testing and internal deployment pipelines — these aren't industry-standard tools, you'll learn them here.

Key job responsibilities
- Design and build the Alarm Notification Reduction Platform: systems that intelligently suppress, correlate, and deduplicate millions of alarms across hundreds of data centers, turning a firehose into a focused, actionable signal stream for operations engineers

- Apply Amazon Bedrock to historically intractable operational problems: natural-language summaries of complex alarm sequences, automated root cause hypotheses, and pattern detection across alarm data. This is Invent and Simplify in practice. This is an applied engineering role — you'll be integrating and orchestrating AI services, not building or training models

- Own the Automated Triage and Ticketing Engine: systems that automatically classify, prioritize, and route alarms to the appropriate data center engineering operations teams with contextual information for faster resolution

- Define and evolve cloud infrastructure using AWS CDK, ensuring deployment pipelines are robust, repeatable, and secure across multiple regions

- Drive architectural decisions for next-generation systems, evaluate build-vs-integrate tradeoffs, define API contracts with partner teams, and author design documents that set multi-quarter direction

- Actively mentor the team of 8 SDE1s and SDE2s, lead design reviews, raise the bar on engineering practices, and foster a culture where engineers grow in both skill and ownership. This is a core requirement, not a nice-to-have

A day in the life
Your morning might start with a standup where you discuss progress on a new alarm correlation service, then shift into a design review where you're coaching an SDE2 through their first large-scale system design. After lunch, you spend a focused block writing TypeScript CDK constructs to deploy a new alarm analysis pipeline, then review a teammate's code for a Python Lambda function that processes alarm metadata. You join a cross-team sync with data center operations stakeholders to understand emerging alarm patterns from a new hardware deployment — sitting with the actual engineers who receive these alarms and hearing firsthand what's noise and what's signal. You wrap up by updating a design document for the next iteration of the notification reduction algorithm and sketching out an approach for integrating generative AI into the triage workflow.

On-call rotations are shared across the team (approximately once every 6-8 weeks), with runbooks and clear escalation paths. The team deploys to production multiple times per week using automated CI/CD pipelines with pragmatic testing, excellent alarm tuning, and developer-friendly deployment schedules leading to minimal out-of-hours engagements.

At 6 months, you've developed the technical strategy for the team. You're providing technical guidance on designs, driving more rigorous design reviews, and engineers are coming to you as a trusted resource for architectural decisions. You have a clear picture of the problem space and have started shaping the roadmap for GenAI in production.

At 12 months, you're driving with autonomy and authority. You own the team's technical direction. Engineers' growth under your mentorship is visible. GenAI-powered features are in production and delivering measurable value to data center operations engineers.

About the team
SKG sits within the DC BRIDGE organization, which builds software platforms that support Amazon's data center engineering operations worldwide. Our systems directly impact the reliability and efficiency of the physical infrastructure that powers AWS and Amazon's global services. The team is led by Eleanor Scott and operates with high ownership and autonomy over our services end-to-end.

Today the Seattle team is 8 SDEs — a mix of SDE1s and SDE2s — and you'd be joining as the senior technical leader. The team needs someone who can define architectural direction, establish engineering best practices, and invest meaningfully in mentoring engineers who are early and mid-career. Your influence will be felt in every design review, every architectural decision, and every engineer who grows under your guidance.