Job description

Amazon Leo is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. The Role This role is for a Software Engineer who will design, implement, and operate globally distributed systems that enable Leo to achieve low single-digit-second query responses within a near real-time analytics layer or lakehouse, and to support agentic AI capabilities on top. You’ll build these systems using the latest AWS technologies and best-in-industry software engineering practices. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities - Architect and implement a scalable, cost-optimized S3-based Data Lakehouse that unifies structured and unstructured data from disparate sources. - Architect and implement a scalable, cost-performance-optimized OLAP-based analytics layer - Establish metadata management with automated data classification and lineage tracking. - Design and enforce standardized data ingestion patterns with built-in quality controls and validation gates. - Architect a centralized metrics repository that becomes the source of truth for all Leo metrics. - Implement robust data quality frameworks with staging-first policies and automated validation pipelines. - Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns. - Develop intelligent orchestration for metrics generation workflows with comprehensive audit trails. - Lead the design of semantic data models that balance analytical performance with AI retrieval requirements. - Implement cross-domain federated query capabilities with sophisticated query optimization techniques. - Architect a globally distributed vector database infrastructure capable of managing billions of embeddings with consistent sub-100ms retrieval times. - Design and implement hybrid search strategies combining dense vectors with sparse representations for optimal semantic retrieval. - Establish automated compliance validation frameworks ensuring data handling meets Amazon's security standards. A day in the life This role is for a Software Development Engineer who will build new cloud services and APIs that facilitate and orchestrate the Leo AI Foundations—enabling intelligent software operation across Leo devices such as satellites, ground gateways, and customer terminals. You will design and deliver low-latency, highly scalable architectures that are critical to providing high-quality internet service and AI capabilities to customers. About the team Amazon Leo AI Foundations builds the intelligent cloud backbone that powers AI-driven decision making across Amazon’s Leo constellation — from satellites and ground gateways to customer terminals. Our team designs and operates large-scale data and compute systems that enable training, inference, and agentic intelligence for optimizing network performance, routing, and user experience in real time. We combine expertise in distributed systems, data lakehouse architectures, and applied machine learning to deliver scalable, low-latency AI capabilities that integrate seamlessly with Leo's software-defined space and ground systems. We move fast, innovate boldly, and work across boundaries to make global connectivity smarter and more efficient. - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent 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 amazon.jobs for more information. If the country/region you’re applying in isn’t 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 amazon.jobs . USA, WA, Redmond - 143,700.00 - 194,400.00 USD annually

Requirements

Must-haves

Key job responsibilities
Architect and implement a scalable, cost-optimized S3-based Data Lakehouse that unifies structured and unstructured data from disparate sources.
Architect and implement a scalable, cost-performance-optimized OLAP-based analytics layer
Establish metadata management with automated data classification and lineage tracking.
Design and enforce standardized data ingestion patterns with built-in quality controls and validation gates.
Architect a centralized metrics repository that becomes the source of truth for all Leo metrics.
Implement robust data quality frameworks with staging-first policies and automated validation pipelines.
Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns.
Develop intelligent orchestration for metrics generation workflows with comprehensive audit trails.
Lead the design of semantic data models that balance analytical performance with AI retrieval requirements.
Implement cross-domain federated query capabilities with sophisticated query optimization techniques.
Architect a globally distributed vector database infrastructure capable of managing billions of embeddings with consistent sub-100ms retrieval times.
Design and implement hybrid search strategies combining dense vectors with sparse representations for optimal semantic retrieval.
Establish automated compliance validation frameworks ensuring data handling meets Amazon's security standards.
A day in the life
About the team
3+ years of non-internship professional software development experience
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience programming with at least one software programming language
3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Bachelor's degree in computer science or equivalent
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, WA, Redmond - 143,700.00 - 194,400.00 USD annually

Nice-to-haves

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Keywords to mirror

aiawsmachine learning

Platform: amazon
Effort: medium

Benefits

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Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave