Software Development Engineer, Applied AI Solutions

Amazon • Mountain View, CA

20h

About The Position

As part of the AWS Applied AI Solutions organization, the team aims to provide business applications leveraging Amazon’s experience to accelerate customer businesses through intuitive and differentiated technology solutions. AWS Physical AI specifically builds a platform to help companies developing autonomous systems validate their safety-critical applications. This involves automating the creation of test scenarios, generating synthetic sensor data, and enabling simulation-based validation to cover edge cases difficult to capture with real-world data. The role spans the full lifecycle of autonomous systems development, from data curation and model training to simulation-based validation and deployment monitoring. As a Software Development Engineer on the Physical AI team, you will build core capabilities to transform operational design specifications into realistic synthetic scenarios, sensor data, and validation workflows. This includes working with generative AI models trained on real-world operational data to create realistic agent behaviors, object interactions, and environmental conditions for exploring safety-critical situations. The work directly enables validation engineers to achieve comprehensive test coverage, significantly reducing manual effort. The team collaborates with other Applied AI Solutions teams, SageMaker teams, and leading simulation platform providers, valuing technical excellence, customer obsession, and systematic problem-solving. This position offers opportunities to shape the future of autonomous systems validation, work with generative AI technologies, and deliver measurable impact to customers deploying safety-critical autonomous systems at scale.

Requirements

• 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
• 1+ years of software development engineer or related occupational experience
• 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
• 1+ years of Object Oriented Design experience
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
• Experience programming with at least one software programming language

Nice To Haves

• 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

Responsibilities

• Design and implement scenario generation pipelines that transform operational design specifications into diverse scenario variations with comprehensive coverage analysis.
• Build generative AI model integration layers that leverage real-world operational data to create realistic behaviors while maintaining physical plausibility constraints for agent dynamics, sensor characteristics, and environmental physics.
• Develop export connectors for industry-standard simulation platforms that handle format compatibility, authentication, and data transfer.
• Create synthetic sensor data generation systems that produce multi-modal outputs (MP4 video, PCD/LAS point clouds, radar data) with accurate sensor characteristics and metadata tracking for validation traceability.
• Implement coverage analysis algorithms that identify gaps in generated scenario distributions and recommend generation parameters to achieve systematic coverage.
• Integrate with SageMaker for perception model training workflows and visualization tooling for validation coverage reporting.
• Review generation quality metrics from customer validation campaigns, analyzing scenario success rates and identifying opportunities to improve edge case coverage.
• Participate in a design review for the next iteration of a specification parser, discussing how to handle region-specific rules and regulatory requirements.
• Pair program with a teammate on implementing physics-based validation checks that verify generated scenarios meet dynamics constraints and behavioral plausibility.
• Join a customer call to understand their specific validation challenges and gather requirements for specialized sensor modalities.
• Optimize a generation pipeline for scalability, balancing generation quality with compute costs for large scenario volumes.
• Mentor a junior engineer on generative AI model integration patterns and reviewing pull requests for the simulation platform connector framework.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level