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Amazon · Seattle, WA

# AI/ML Engineer, Amazon Global Data Center Ops Central Insight and Analytics Team

US, WA, Seattle Data & Analytics 

Listed on Amazon’s official careers site. Posted August 25, 2026. Check that it is still open and apply there.
[Apply on Amazon’s careers site →](https://www.amazon.jobs/en/jobs/10513234/ai-ml-engineer-amazon-global-data-center-ops-central-insight-and-analytics-team)

[OpenNash Jobs](https://jobs.opennash.com/) / [Amazon](https://jobs.opennash.com/companies/amazon/) / AI/ML Engineer, Amazon Global Data Center Ops Central Insight and Analytics Team

## Job description

We are looking for an AI/ML Engineer to build, deploy, and operate the ML/AI systems that power the agentic decision intelligence workflow we are building. You are the person who takes a model from a notebook to production, builds the LLM integration layer, implements RAG pipelines, creates evaluation frameworks, and ensures our AI systems are reliable, observable, and continuously improving.

This is a hands-on engineering role with deep ML/AI focus — you write production code that runs AI systems, not research papers. If you love the intersection of ML infrastructure, LLM applications, and production engineering, this role is for you.

### Key job responsibilities

- Build and maintain LLM-powered components: structured reasoning chains, narrative generation, recommendation rationale

- Implement and optimize prompt engineering pipelines with version control, A/B testing, and regression detection

- Build RAG (Retrieval-Augmented Generation) systems that ground LLM outputs in operational data, historical playbooks, and domain knowledge

- Build guardrails, validation layers, and output parsing for LLM responses. Optimize latency, cost, and quality trade-offs across LLM providers

- Deploy ML models to production.

### Implement model monitoring

drift detection, performance degradation alerts, automated retraining triggers

- Build A/B testing infrastructure for model experiments. Manage model versioning, rollback, and canary deployment. Ensure SLA compliance for inference latency and availability

- Own the operational health of AI/ML services: monitoring, alarming, on-call, incident response, observability across the AI stack (prompt traces, latency histograms, token usage, error rates)

- Write comprehensive tests (unit, integration, end-to-end) for ML pipelines

## At a glance
- Posted by the employer: Aug 25, 2026
- First seen by OpenNash: Oct 11, 2026
- Last checked: Oct 11, 2026
- Listed for: 47 days
- Location: US, WA, Seattle[Apply on Amazon’s careers site →](https://www.amazon.jobs/en/jobs/10513234/ai-ml-engineer-amazon-global-data-center-ops-central-insight-and-analytics-team)

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