3.8 Software Engineer: Infrastructure and Tools

Our salary range is highly competitive with the market, but we take into consideration an individual's background and experience in determining final salary.

Base pay offered may vary depending on geographic location, job-related knowledge, skills, and experience.

In addition to competitive compensation, FieldAI offers comprehensive benefits, equity participation, and the opportunity to contribute to cutting-edge advancements in AI and robotics.

• Design, build, and maintain core infrastructure components such as CI/CD pipelines, build systems, monitoring tools, and deployment frameworks.
• Develop and implement scalable solutions for service reliability, observability, and performance.
• Collaborate with development teams to optimize infrastructure for high availability and fault tolerance.
• Automate infrastructure provisioning and management using tools like Ansible or similar.
• Improve system efficiency by automating recurring tasks and eliminating manual processes.
• Monitor system performance, troubleshoot issues, and ensure optimal uptime and security.
• Maintain and enforce best practices in system design, security, and code quality.
• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent work experience).
• 3+ years of experience in software engineering, DevOps, or infrastructure roles.
• Strong programming/scripting skills in languages such as Python, TypeScript, or similar.
• Experience with cloud platforms (AWS, GCP, Azure) and container orchestration.
• Familiarity with infrastructure-as-code tools (AWS CDK, etc.).
• Knowledge of monitoring and logging systems (e.g., Prometheus, Grafana, Sentry).
• Solid understanding of networking, Linux systems, and security best practices.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.
• Familiarity with robotics systems or infrastructure to support robotic applications (e.g., ROS, real-time systems, sensor integration).
• Exposure to distributed systems and microservices architectures.
• Background in site reliability engineering (SRE) practices.