Software engineer on AWS's Data Center Gen AI team, building AI/ML platform features — LLM/agent integrations, serverless backends, and React frontends — that automate technician workflows across AWS's global data centers. Core stack includes AWS serverless (Lambda, DynamoDB, CDK), LangChain/RAG, and TypeScript.
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.
About the Data Center Gen AI Team
Join the Data Center Gen AI team, where we build generative AI solutions for AWS data centers. Our systems orchestrate physical work processes across AWS's worldwide data centers, directly impacting millions of customers who rely on AWS services.
Position Impact
You'll contribute to transforming data center operations through AI/ML innovations, helping build the platform primitives that dozens of teams across the Data Center Community rely on. You'll work on developing intelligent systems that optimize technician workflows, automate decision-making processes, and enhance operational efficiency across AWS's global infrastructure while supporting AI-powered capabilities for a 30K+ globally distributed user base.
Strong familiarity with one or more of the following:
- Generative AI / Agentic Systems — LLM integration, prompt engineering, RAG architectures, tool-calling patterns, agent frameworks (Strands, LangChain)
- Full-Stack Serverless Engineering — AWS Lambda, API Gateway, CloudFront, DynamoDB/RDS, EventBridge, SQS, CDK Infrastructure-as-Code
- Frontend & SDK Development — React, TypeScript, Cloudscape Design System, component library development, streaming interfaces (SSE)
- Search & Knowledge Systems — OpenSearch/Elasticsearch, vector embeddings, hybrid retrieval, document processing pipelines, semantic chunking
- ML & Data Engineering — SageMaker, time-series analysis, anomaly detection, classification models, feature engineering, ETL pipelines
- Platform & DevOps — CI/CD pipeline development, progressive deployment, synthetic monitoring, observability (CloudWatch, X-Ray, OpenTelemetry)
Ideal Candidate Profile
- Thrives in ambiguous environments and is eager to learn and adapt quickly
- Demonstrates a bias for action with the ability to deliver results in fast-paced settings
- Builds and maintains solid technical depth while staying customer-focused
- Shows genuine curiosity and enthusiasm for AI/ML advancements
- Has working knowledge of AI/ML technology application (LLMs, agents, RAG, Skills, ML models)
- Takes ownership of features and components end-to-end, driving them to completion with guidance from senior engineers
- Balances pragmatic execution with creative problem-solving
This role offers the opportunity to contribute to the future of AWS data center operations through innovative AI/ML solutions while working with advanced technologies at unprecedented scale.
Key job responsibilities
- Design and develop AI/ML platform features and solutions, contributing to systems that serve both data center operations and engineering teams
- Own end-to-end delivery of features and components, including AI integrations, deployment pipelines, and user-facing interfaces for non-ML experts
- Collaborate with senior engineers and cross-functional partners to integrate ML solutions into existing DC workflows, ensuring system quality and scalability
- Write clean, well-tested, and maintainable code while actively contributing to improvements in development processes, particularly for GenAI development and deployment
- Participate in technical design discussions and code reviews, bringing a customer-focused perspective to architectural decisions
- Design and implement reusable components and tools that enhance team productivity and system reliability
- Stay current with AI/ML advancements and proactively identify opportunities to apply new techniques to data center challenges
About the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.