Senior Software Engineer - Engineering Productivity Systems
About The Position
About the Team Our Simulation team is responsible for building the foundational infrastructure that powers large-scale simulations critical to autonomous system development. We work at the intersection of cloud computing, distributed systems, and core simulation. Our simulations are used daily across the company: by QA engineers verifying component-level quality, by autonomy engineers investigating unexpected behavior, by ML teams validating new model versions, and by safety analysts and data scientists who analyze thousands of simulated scenarios and metrics to assess system readiness. The simulator is modular and supports both full-system and component-level runs. It operates at scale on distributed compute clusters, enabling us to simulate far more situations than we can cover on the road. About the Role As a Simulation Backend Engineer, you'll design, build, and optimize the systems that power our distributed simulation workloads. You will work on everything from data pipelines and orchestration to cloud-based storage and microservice infrastructure. You’ll play a pivotal role in enabling our simulation engineers and researchers to run massive experiments with high efficiency and reliability.
Requirements
- 3+ years of experience building backend services in production environments.
- Proficiency in at least one of the following languages: Python (preferred), Java, or Go.
- Deep understanding of cloud-native architecture and distributed systems.
- Hands-on experience with key technologies such as AWS (S3, EKS), Redis, Kafka, Postgres, and Terraform.
- Experience with containerization and orchestration (e.g., Docker, Kubernetes).
- Candidates are required to be authorized to work in the U.S.
- The employer is not offering relocation sponsorship, and remote work options are not available.
Responsibilities
- Architecting and implementing backend services for managing and orchestrating simulation jobs at scale.
- Designing efficient data storage and retrieval pipelines using systems like S3, Postgres, and Redis.
- Building and maintaining distributed messaging systems with Kafka for robust event-driven pipelines.
- Defining infrastructure as code using Terraform to automate deployment and scaling in AWS clusters.
- Collaborating with simulation engineers and infrastructure teams to ensure robust integration and performance.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
251-500 employees
