Software Engineering Internship

Hypercubic•San Francisco, CA

4d•Onsite

About The Position

The world’s most critical infrastructure—banking, airlines, utilities—is held together by millions of lines of COBOL and mainframe logic written decades ago. The engineers who built it are retiring and the documentation is fading. These systems are "too big to fail" and "too complex to change," leaving global infrastructure frozen in the 1970s. At Hypercubic, we’re building AI systems that can understand, reason about, and rearchitect large-scale legacy applications. We work at the intersection of program analysis, knowledge extraction, and agentic systems, applied to some of the most critical enterprise software in the world. Learn why we're excited about mainframe modernization.

Requirements

Students with unusually high slope and strong engineering taste.
Strong programming fundamentals and can learn unfamiliar tools and systems quickly.
Demonstrated abilities through ambitious projects, research, open-source contributions, internships, or exceptional coursework.
Comfortable with uncertainty and enjoy figuring out what to build before determining how to build it.
Think in systems and feedback loops, not just features.
Can move fast and slow—prototyping ideas in hours, then developing the most promising ones to a high-quality bar.
Can reason clearly about technical decisions and communicate your thinking.
Want to become world-class at AI engineering.
Bias for action and thrive in fast-moving environments.
Open to currently enrolled undergraduate and graduate students of any year, degree program, or major.
Candidates must already be authorized to work in the United States. We can support CPT and OPT, but cannot sponsor new visas.

Nice To Haves

Experience building complex agentic products, infrastructure, or autonomous systems.
Strong testing intuition, including experience with TDD or property-based testing.
Experience building and maintaining production-grade software.
Exposure to legacy systems (especially mainframes or COBOL), compilers, program analysis techniques, or high-performance computing (HPC).
Familiarity with enterprise software constraints.

Responsibilities

Own and ship a high-impact engineering project end to end.
Rapidly prototype new concepts and features to validate ideas before full implementation.
Build AI-driven systems, including agent workflows, evaluations, program-analysis tooling, backend infrastructure, and user-facing features.
Translate ambiguous problems into concrete experiments, constraints, and working systems.
Contribute to engineering standards around testing, reliability, and code quality.
Work directly with the CTO on technical and product decisions, taking on greater ownership as you earn trust.
Collaborate with subject-matter experts and customers across industries including banking, insurance, airlines, and utilities.