Early In Career - Software Engineer

Key Responsibilities

• Collaborate with cross-functional teams to design, develop, and deploy software solutions with agility and rapid iteration.
• Use and experiment with AI-assisted development tools (e.g., Cursor, Claude Code, internal agents) to boost productivity and improve code quality.
• Help define and evolve new engineering practices that leverage AI for code generation, testing, documentation, refactoring, and operations.
• Write clean, maintainable code and participate in peer reviews and team design discussions.
• Contribute to the automation of development, deployment, and monitoring processes as part of a DevOps culture.
• Continuously learn and apply new AI technologies, frameworks, and techniques that can enhance developer workflows.
• Participate in team retrospectives and help drive improvements in team velocity and product quality.

Required Qualifications

• Must be a US Citizen.
• Bachelor's degree earned between May/June 2024 and May/June 2025 with ~1 year of professional experience.
• (Internships, Co-ops, Research Assistant, TA roles do not count towards professional exp).
• Master's degree earned between Dec 2025 and May/June 2026 with at least 1 year of professional exp prior to Masters.
• Degree focus must be Machine Learning, Computer Science, Cybersecurity, Data Science, Artificial Intelligence, Software Engineering or something similar.
• Strong programming skills in either Python, Java or C/C++.
• Familiarity with Networking fundamentals (for Embedded & Distributed Systems positions).
• An understanding of the fundamentals of Computer Science.
• Exemplify strong initiative and ability to work independently with limited direction.
• Able to work cross functionally with other engineers, researchers and Product Managers.
• Excellent communications skills and an interest in Cybersecurity.

Preferred Qualifications

• Exposure to large language models (LLMs) or AI/ML APIs, even through personal projects.
• Familiarity with cloud environments (GCP, AWS or Azure) and containerized development (e.g., Docker, Kubernetes).
• Experience with modern developer tools such as CI/CD pipelines, observability platforms, and infrastructure-as-code.