Software Engineer – AI Platforms & Edge Computing

Software Engineer – AI Platforms & Edge Computing Key Responsibilities

• Develop and maintain software components using C/C++, Go, or Python, with guidance from senior engineers.
• Contribute to building and integrating API-based middleware, databases, and edge/cloud services.
• Implement and support containerized applications using Docker and Kubernetes for development and deployment.
• Collaborate on the development of Infrastructure-as-Code (IaC) scripts for automated deployment and configuration.
• Assist in integrating AI/ML pipelines and inference runtimes into edge or embedded systems.
• Work with networking protocols (TCP/IP, HTTPS) to ensure secure and efficient communication between distributed components.
• Participate in code reviews, testing, and debugging to maintain high-quality, production-ready code.
• Collaborate using Git in a team-based, agile software development environment.
• Help automate build, deployment, and testing workflows using CMake, BASH scripting, and CI/CD tools.
• Learn and contribute to system monitoring, troubleshooting, and performance optimization.

• 1–3 years of professional software engineering experience (or strong internship/project experience).
• Proficiency in at least one of: C/C++, Go, or Python.
• Familiarity with Linux development environments and basic scripting (BASH, Python).
• Basic understanding of network protocols (TCP/IP, HTTPS).
• Exposure to containerization (Docker) and/or orchestration tools (Kubernetes).
• Experience with Git or similar version control systems in collaborative projects.
• Eagerness to learn edge computing, cloud platforms (AWS, GCP, Azure), and AI system integration.
• Strong problem-solving skills and attention to detail.
• Applicants must be authorized to work in the United States without the need for current or future employer sponsorship.

• Experience building edge AI platforms, including model serving, data preparation
• Hands‑on experience or coursework related to AI/ML model deployment, data streaming, or edge devices.
• Knowledge of Dev Ops, CI/CD pipelines, or Git Ops workflows.
• Exposure to build systems like CMake or Bazel.
• Understanding of software design principles, distributed systems, or real‑time computing.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field; or equivalent hands‑on experience.

• Shape the foundation of an AI and edge computing platform at the heart of a high‑impact startup.
• Work on cutting‑edge technology bridging embedded systems, cloud computing, and AI applications.
• Collaborate with world‑class engineers solving complex distributed systems challenges.
• High ownership, fast iteration, and opportunities to lead architecture and innovation initiatives.
• Competitive compensation, equity options, and a culture that values innovation and technical excellence.