Description

How often have you had an opportunity to be an early member of a team that is tasked with solving a huge customer need through disruptive, innovative technology, reinventing an industry? Are you passionate about building cutting-edge software solutions that leverage the power of Generative AI? Do you want to be at the forefront of transforming how Amazonians work and collaborate? If so, we want to hear from you!

The Foundational AI — Quick & Automation Platform Team drives AI adoption and builds the automation infrastructure that powers Amazon Quick Suite internally. We are responsible for launching Quick Suite features to 450,000+ Amazonians, building custom connectors and integrations (e.g., GRASP), and developing platforms like Ciphr and ORCA for AI-powered workflow automation. Our mission is to use AI to measurably improve productivity for every Amazonian.

Role Overview
We are looking for a talented SDE2 to help us build and scale the AI-powered automation platform behind Amazon Quick Suite. You will design and deliver features that enable natural language workflow automation, agentic AI capabilities, and enterprise integrations — all operating at massive scale. You will own end-to-end delivery of projects, contribute to technical direction, and work at the intersection of AI/ML, distributed systems, and developer productivity.
Key Responsibilities

- Design & Build AI-Powered Systems: Architect and implement scalable services that use Quick Flows, Quick Automate, and custom agent capabilities
- Build Integrations & Connectors: Design and develop connectors that enable Quick Suite to interact with enterprise tools and internal Amazon systems
- Own End-to-End Delivery: Drive features from design through deployment, including operational excellence and monitoring
- Scale for Impact: Build systems that serve 450,000+ internal users and external AWS customers with high availability and low latency
- Collaborate Across Teams: Partner with Quick Suite product teams, AWS service teams, and internal customers to define requirements and deliver solutions
- Raise the Bar: Mentor junior engineers, improve engineering practices, and contribute to team-wide technical standards


Preferred Qualifications
- Experience with AI/ML systems, LLM-based applications, or agentic AI frameworks
- Experience with AWS services (e.g., Lambda, DynamoDB, S3, SQS, ECS, Bedrock, Step Functions)
- Experience building workflow automation or orchestration platforms
- Familiarity with CI/CD pipelines, infrastructure-as-code, and operational best practices
- Experience with enterprise integration patterns and connector frameworks
- Track record of delivering complex, ambiguous projects independently
- Strong written and verbal communication skills

Why Join Us?
- Build the future of AI at work: Shape how AI agents and automation transform productivity for hundreds of thousands of users
- High-impact, high-visibility work: Our team's features are used daily by Amazonians across the company and by AWS customers globally
- Strong ownership culture: Own your projects end-to-end with real autonomy and accountability
- Growing team with big ambitions: Be part of a team that launched Quick Suite internally and is expanding its platform capabilities

Key job responsibilities
Key job responsibilities

1. Design and implement robust, scalable architectures for AI-powered applications.
2. Develop high-performance backend services to support AI model integration and data processing.
3. Create and maintain RESTful APIs for seamless interaction between AI models and front-end applications.
4. Design and implement microservices architecture to ensure modularity and scalability of the system.
5. Optimize code and database queries for handling large-scale data and high-concurrency scenarios.
6. Partner with UX/UI designers to understand user workflows and translate them into intuitive and user-friendly features
7. Leverage AWS services to build and deploy cloud-native applications.
8. Ensure the implementation of robust security measures and compliance with data privacy regulations.
9. Conduct thorough code reviews and mentor other engineers on the team to maintain high code quality standards.
10. Participate in agile development processes, including sprint planning, daily stand-ups, and retrospectives.