Software Engineer - Backend

Driver•Austin, TX

1d•Hybrid

About The Position

At Driver, we're building systems that turn source code into human language. The tech stack includes a core compiler-like engine, a heavily asynchronous/distributed backend server, and a frontend web application that provides a rich user experience. As a backend engineer, you will help scale and extend our backend, build new product functionality, and make sound architectural decisions that keep pace with a fast-growing system. Driver is an early-stage but fast-growing startup. As such, we take advantage of that which startups can excel: delivery speed, flexibility, and enjoying working with a close-knit team. Organizational and engineering values at Driver include first-principles thinking, correct by construction, writing things down, experimentation and iteration, pragmatism, commitment to effective communication and transparency, autonomy, and ambition.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field.
Minimum 3 — 5 years as a backend engineer.
Experience building and scaling backend systems, with a strong grasp of distributed systems fundamentals (queuing, consistency trade-offs, async task orchestration).
Proficient in Python; experience with at least one statically typed language (e.g., Rust, Go, Java, C++) and a strong grasp of data-structure-oriented design — you think carefully about types, contracts, and correctness, not just getting code to run.
Strong API design instincts: knows how to define clean, stable interfaces and contracts that are easy to consume and hard to misuse.
Strong experience with asynchronous programming paradigms.
Strong understanding of data model design, particularly for relational databases.
Strong instincts for architecture: knows what good looks like, can identify fragile code and tests before they become problems.
Experience building monitoring, logging, and testing in larger backend systems.
Experience building and maintaining REST APIs at scale.
Experience with task orchestration and distributed job queue technologies.
Actively embraces AI-assisted development — uses agentic coding tools as a productivity multiplier and is energized by, not resistant to, this shift in how software is built.

Nice To Haves

7+ years experience preferred.
Experience building MCP-style service interfaces.
Experience with containerization and container orchestration (Docker, Kubernetes).
Experience with identity and access management (IdM) systems and integrations.
Experience working with LLM model APIs and agent toolchains; understanding of how context flows through an agentic system.

Responsibilities

Contribute to building an efficient and scalable backend data model.
Build and maintain critical backend integrations (e.g., VCS providers).
Build and maintain the backend web server.
Design, build, and maintain internal APIs for our web application.
Build and maintain backend APIs for our Model Context Protocol (MCP) products.
Build foundations that scale.
Interface with the transpiler team on: Efficient data model for transpiler content. Asynchronous and distributed implementation for transpiler task orchestration.
Bring strong architectural instincts to the team: Identify and address scalability, correctness, and maintainability risks early.
Write clean, well-structured code that is readable by both humans and LLMs.
Distinguish robust tests from fragile ones; build systems that are easy to verify.
Embrace AI-assisted development: Use agentic coding tools as a core part of your workflow to accelerate delivery. Apply your architectural judgment to validate, guide, and extend AI-generated code.
Interface with the frontend team on: Co-design the internal API for the FE and important interface contracts. The best way to model data communicated between BE and FE.
Interface with the DevOps/Infrastructure team on: Distributed task orchestration implementation. Container and distributed job implementation.
Communicate effectively with team members and across key team interfaces.