At Driver, we’re building systems that turn source code into human language. Our core technology, the Driver Transpiler, blends traditional compiler elements with LLM content generation to generate exhaustive, structured documentation of software. As a transpiler engineer, you will help build the foundations of this system.
About DriverWe’re an early-stage startup backed by Y Combinator and Google Ventures that combines first principles technical approaches and applied LLM expertise to tackle context engineering at scale. Driver builds the context layer for employees and AI agents alike to use in developing software.
Working at DriverDriver is an early-stage but fast-growing startup. As such, we take advantage of what startups can excel at: delivery speed, flexibility, and enjoying working with a small, close-knit team.
Organizational and engineering values at Driver include first-principles thinking, correctness by construction, writing things down, experimentation and iteration, pragmatism, a commitment to effective communication and transparency, autonomy, and ambition.
About the Role
Our core innovation, the Driver Transpiler, treats software explanation as a compilation problem. Instead of emitting machine code, it emits human language, and has a compiler architecture: we take in code, analyze it in the structured way a compiler does (parsing symbols, building symbol tables and syntax trees, and performing multiple passes), and output human language documentation exhaustively and at arbitrary scales.
This architecture fuses traditional compiler-like static analysis and data structures with highly structured use of large language models (LLMs). Optimization passes and intermediate representations (IRs) mean very different things for us, so experience with traditional compilers is not required but may be helpful.
This is a foundational role: the transpiler is the core of our product and our differentiation. You’ll collaborate closely with our CTO and engineering leadership to expand its capabilities and shape the company’s technical direction. You’ll also have an opportunity to work in a unique cutting-edge space where traditional compiler ideas, applied LLM expertise, and agentic designs meet.
Key Responsibilities
- Core contributor to the Driver Transpiler:
- Static analysis (e.g., with tools like tree-sitter) to parse and process code from any language in the transpiler frontend.
- Build and manipulate syntax trees and symbol table representations.
- Build templating engines and strategies for structured content generation with LLMs in the transpiler backend.
- Improve scalability and robustness.
- Contribute to the overall compiler architecture and feature roadmap.
- Own language specialization end-to-end for various languages.
- Build language specializations (optimizations and bespoke syntax/semantic support) for individual languages.
- Balance a language’s specific syntax/semantics, expectations of the community, and consistency in the Driver experience.
- Advance the design and implementation of language specialization as a whole.
- Contribute to our internal AutoDocs engine:
- Later stage compiler subsystem that builds complex single documents from wide ranging inputs and is exposed to users directly.
- Joint optimization with earlier stages of the transpiler.
- Expand the capabilities of the transpiler.
- New forms of intermediate representations (IRs) and content pre-computed in the transpiler for downstream applications.
- Introduce new optimizations and new passes of the transpiler.
- Better use of syntax trees and call graphs to link content.
- Communicate effectively with others on the team, such as backend engineers, to evaluate, test, and deploy transpiler updates.
Education: Bachelor's degree in Computer Science, Engineering, or a related field.
Experience: Minimum 3 — 5 years as a software engineer or similar (e.g., compiler/language developer).
Required Technical Skills
- Proficient in multiple languages, including Python.
- Experience with asynchronous programming in Python.
- Experience and skill in building software systems and larger architectures.
- Experience with graph constructs such as directed acyclic graphs (DAGs) and algorithmic solutions that use them.
- Familiarity with LLM and agent toolchains, prompt engineering, direct LLM API calls, and use of structured output.
- Experience modeling data, validating data, and implementing transformations on data in software development using custom data structures and tools like Pydantic.
- Comfort and desire to work in ambiguous and new problem spaces without well-established solutions.
Preferred and Nice-to-Have Technical Skills
- Previous use of tree-sitter or similar parsing tools.
- Experience with documentation rendering and generation tools such as Doxygen, Javadoc, Rustdoc, Sphinx, etc.
- Interest in programming languages and compilers.
- Experience working on traditional compilers or code/static analysis.
- Experience with strong, static type systems like those in Rust, OCaml, Scala, or Haskell.
- Experience with functional programming concepts.
- Experience with or interest in programming language theory.
- Experience with database/data model designs.
- Experience using and building templating engines or configuration schemas.
You’ll work on technology at the intersection of language theory, compiler design, and generative AI, building systems that expand how both humans and machines understand code.
You’ll also have an outsized impact: this is a core product role in a fast-growing company, where the things you build will directly shape how engineers and AI collaborate in the next decade.
- Competitive Compensation Packages - Cash & Equity
- Flexible Work Culture
- Unlimited Time Off + 12 Paid Company Holidays
- Insurance - Health, Dental, & Vision
- Life Insurance & FSA Accounts
- 401(k) Retirement Accounts - Traditional, Roth, or Both
- Quarterly Team Offsites
Driver is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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