Software Development Manager, Amazon Leo AI Foundations

Amazon Amazon · Big Tech · Redmond, WA · Software Development

Software Development Manager for Amazon Leo AI Foundations, responsible for designing, implementing, and operating globally distributed systems for a low Earth orbit satellite network. The role focuses on building near real-time analytics, a data lakehouse, and supporting agentic AI capabilities, including architecting a vector database with sub-100ms retrieval times and hybrid search strategies. The team builds the intelligent cloud backbone for AI-driven decision making across the Leo constellation, optimizing network performance and user experience.

What you'd actually do

  1. Architect and implement a scalable, performance-optimized OLAP-based analytics system.
  2. Architect and implement a scalable, cost-optimized Data Lakehouse that unifies structured and unstructured data from diverse sources.
  3. Architect a centralized metrics repository that becomes the source of truth for all Leo metrics.
  4. Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns.
  5. Implement cross-domain federated query capabilities with sophisticated query optimization techniques.

Skills

Required

  • 3+ years of engineering team management experience
  • 7+ years of engineering experience
  • 8+ years of leading the definition and development of multi tier web services experience
  • 3+ years of Software Engineer, Software Developer, or related occupational experience
  • 1+ years of providing technical leadership and project management for all aspects of the software development lifecycle experience
  • 1+ years of developing large-scale, multi-tiered distributed software systems using Java, C#, or C++ experience
  • 1+ years of developing large-scale, multi-tiered distributed software systems using service-oriented architecture experience
  • 1+ years of developing large-scale, multi-tiered distributed software systems using distributed programming experience
  • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
  • Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
  • Experience partnering with product or program management teams

Nice to have

  • Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
  • Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

What the JD emphasized

  • globally distributed systems
  • agentic AI capabilities
  • low single-digit-second query responses
  • near real-time analytics layer or lakehouse
  • AI retrieval patterns
  • globally distributed vector database infrastructure
  • billions of embeddings
  • sub-100ms retrieval times
  • hybrid search strategies
  • intelligent software operation
  • low-latency, highly scalable architectures
  • AI-driven decision making
  • large-scale data and analytics systems
  • training, inference, and agentic intelligence
  • real time

Other signals

  • design and implement globally distributed systems
  • support agentic AI capabilities
  • AWS technologies
  • data engineering practices
  • low single-digit-second query responses
  • near real-time analytics layer or lakehouse
  • intelligent orchestration for metrics generation workflows
  • semantic data models that balance analytical performance with AI retrieval requirements
  • globally distributed vector database infrastructure
  • billions of embeddings with consistent sub-100ms retrieval times
  • hybrid search strategies combining dense vectors with sparse representations
  • build new cloud services and APIs that facilitate and orchestrate the Leo AI Foundations
  • intelligent software operation across Leo devices
  • low-latency, highly scalable architectures
  • AI-driven decision making across Amazon’s Leo constellation
  • large-scale data and analytics systems
  • training, inference, and agentic intelligence
  • optimizing network performance, routing, and user experience in real time