AIML Engineer, Amazon Global Data Center Ops Central Insight and Analytics Team

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

- 3 years of non-internship professional software development experience
- Bachelors degree in Computer Science Machine Learning or related field (or equivalent experience)
- 2 years deploying ML models to production environments
- Strong Python proficiency experience with ML frameworks
- Experience with LLM APIs and prompt engineering
- Experience with cloud ML services
- Experience building data pipelines for ML (feature engineering preprocessing training data management)
- Solid software engineering fundamentals (testing CI/CD code review production operations)

- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Experience building RAG systems (vector databases embedding models retrieval pipelines)
- Experience with agent/orchestration frameworks (LangChain LangGraph CrewAI Bedrock Agents or custom)
- Experience with ML evaluation frameworks (especially for generative AI / LLM outputs)
- Experience with time-series ML (forecasting anomaly detection)
- Experience with MLOps tooling (MLflow SageMaker Pipelines Step Functions feature stores)
- Experience with infrastructure-as-code (CDK CloudFormation Terraform)
- Background in operational/infrastructure environments

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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 143700.00 - 194400.00 USD annually