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Torc Robotics

Software Engineer 2

Blacksburg, VAFrom $145.6kmidAdded today

About this role

Design and build large-scale backend services for enterprise data platforms, handling high-volume data ingestion, transformation, and access. Lead architecture decisions, mentor engineers, and optimize cloud infrastructure on AWS while ensuring data governance and system reliability.

What you'll do

  • Design and own backend services supporting data ingestion, tagging, transforming, and querying at scale
  • Develop REST API-driven services for cloud workflows, vehicle testing systems, and enterprise data access
  • Implement data management capabilities including access control, schema validation, caching, and file placement optimization
  • Architect and manage AWS-based infrastructure for backend and data platforms using Lambda, S3, EC2, and other services
  • Lead architecture discussions, define system interfaces and data models for cross-team platforms
  • Mentor engineers and interns on backend systems, troubleshoot operational issues using Datadog, and drive cost optimization initiatives

What they're looking for

  • AWS cloud architecture (Lambda, Step Functions, IAM, S3, EC2)
  • Python backend development and REST API design
  • ETL/ELT pipeline design for large-scale data processing
  • Infrastructure as Code (Terraform, GitHub Actions, CI/CD)
  • Docker, ECR, and ECS containerization and orchestration
  • Data modeling and data governance for distributed systems
  • Monitoring with Datadog and Tableau dashboards
  • System design and architecture leadership
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Torc Robotics

Torc Robotics develops autonomous driving software and systems for trucks. The company is hiring systems engineers, software engineers, and test automation specialists to build validation frameworks, integration environments, and web applications that ensure the reliability and quality of their autonomous vehicle technology.

Website
torcrobotics.com
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Likely interview questions

  • Describe your experience designing AWS-native architectures at scale—what was your largest data ingestion project and how did you handle reliability?
  • Walk us through how you've implemented ETL pipelines; what bottlenecks did you encounter and how did you optimize for throughput?
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