The company is looking to build transformative, AI-driven solutions to tackle complex problems in cybersecurity.
Requirements
- 8+ years of experience building and operating production-grade full-stack applications in cloud environments such as AWS
- 8+ years of experience with software development in both front-end and back-end technologies and with languages such as Java, Python, or Go
- 6+ years of experience with design and architecture, including design patterns, reliability, and scaling of new and existing systems
- Knowledge of AI frameworks such as TensorFlow, PyTorch, and scikit-learn
- Experience with automated deployment and testing tools
- Experience with cybersecurity
- Experience developing market-leading products, specifically in cybersecurity
Responsibilities
- Build full-stack cloud-native systems with robust monitoring, alerting, and fault-tolerant capabilities
- Lead the design, development, deployment, and operation of high-availability software products with agentic AI at their core
- Implement best practices for CI/CD deployments, canaries, telemetry, and automated testing to ensure quality and reliability
- Share skills with the team to utilize new tools and techniques
- Help identify and implement system improvements
- Deliver complete end-to-end solutions using the latest architectural approaches and open-source frameworks and tools
- Operate and maintain production-grade full-stack applications in cloud environments
Other
- Ability to work with automated deployment and testing tools to perform testing and maintenance
- Ability to lead, collaborate, and thrive in a fast-paced and creative environment
- Ability to own products end-to-end, from architecture and coding to deployment, testing, and support
- Bachelor's degree in a CS field and 6+ years of experience in software engineering, or 10+ years of experience in software engineering in lieu of a degree
- Master’s degree in CS, Artificial Intelligence, or a related field (preferred)
- U.S. citizenship required
- Ability to work on camera during interviews and assessments
