Harbinger Motors Inc.
Software Engineer, Enterprise Applications (Backend)
About this role
Harbinger, an innovative EV company, seeks a Backend Engineer to design and scale the infrastructure powering vehicle data management, simulations, and software systems. You'll work on distributed systems, data pipelines, and cloud architecture supporting a mission-driven sustainable technology platform.
What you'll do
- Design and maintain core backend systems for vehicle telemetry, analysis compute, and database management
- Build and manage high-performance APIs (REST, GraphQL, gRPC) for microservice and external integrations
- Implement data pipelines, ETL processes, and storage solutions ensuring data integrity and compliance
- Optimize server performance, resolve bottlenecks, and ensure cloud infrastructure scales under load
- Develop comprehensive testing strategies (unit, integration, load) and troubleshoot complex system issues
- Collaborate with embedded systems engineers, data scientists, and front-end teams on integrated solutions
What they're looking for
- Backend programming (Python, Java, Go, C++, or Node.js)
- Relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis)
- RESTful API design and microservices architecture
- Infrastructure as code (Terraform, Ansible) and containerization (Docker, Kubernetes)
- Cloud platforms (AWS, Azure, Google Cloud)
- Distributed systems design and performance optimization
- Cybersecurity and secure coding practices
- System integration and data pipeline development
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Harbinger Motors Inc.
Harbinger Motors Inc. develops medium-duty electric vehicles and related powertrain systems, with a focus on commercial delivery trucks and advanced driver-assistance capabilities. The company is hiring engineers across manufacturing, thermal analysis, systems architecture, quality assurance, and software testing to build out its EV platform and autonomous driving features.
- Website
- harbingermotors.com
Likely interview questions
- Describe your experience designing and optimizing data pipelines for high-volume telemetry ingestion. How did you ensure data integrity and performance?
- Walk us through a complex distributed system you've built. What were the key challenges in achieving scalability and reliability?