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Software Engineer - Backend at Driver

Role overview

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 3-5 years of backend engineering experience (7+ years preferred).
  • Proficiency in Python and at least one statically typed language (Rust, Go, Java, or C++) with a strong data-structure-oriented design.
  • Strong API design skills with experience in asynchronous programming and distributed systems, including REST APIs and scalable architectures.

Responsibilities

  • Build and maintain a scalable backend data model and critical integrations (e.g., VCS providers) and the backend web server.
  • Design, build, and maintain internal APIs for the web application and the Model Context Protocol (MCP) products; ensure scalable foundations for the system.
  • Interface with the transpiler team on data models and asynchronous task orchestration; collaborate with the DevOps/infrastructure team on distributed deployment and job execution; coordinate with frontend and product teams on APIs and MCP interfaces.
  • Apply architectural judgment to identify scalability, correctness, and maintainability risks early; write clean, well-structured code and robust tests; embrace AI-assisted development to accelerate delivery.

About the company

Driver AI logo

Driver AI

Developer Tools & DevOps Platforms

Driver AI is the new way to write technical documentation. It helps everyone in an organization write interactive documents to explain millions of lines of code in minutes instead of months.Driver AI partners with chip manufacturing, enterprise IT, and software product development teams.Traditionally, these teams spend millions and wait months (sometimes years) to understand their complex technology infrastructure well enough to build on top of it. Instead, Driver AI is a tool that explains complex codebases in minutes vs. months. This enables teams to rapidly accelerate the technical discovery process and save significant resources. Driver AI works by digesting a codebase, organizing it for analysis, and harnessing Large Language Models (LLMs) to generate interactive explanations for executives, product and technology leaders, and developers.Driver AI is a paradigm shift for managing our complex software delivery pipeline. - Executive Vice President, Global Semiconductor Company

Company details

IndustryDeveloper Tools & DevOps Platforms
Company size11 - 50

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Job description

Software Engineer - Backend

Introduction

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.

About Driver

We’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 Driver

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.

Job Overview

Title: Software Engineer – Backend

Location: Remote or Austin, TX

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.

The transpiler generates human language content at large volumes and highly variable levels of abstraction and requires significant asynchronous task orchestration due to the high volume of highly constrained LLM inference calls to external APIs.

Major established components of our backend today include the data model to support the compiler's content generation and coordination with codebase assets in version control system (VCS) providers like GitHub, containerized deployment in a distributed cloud service, and an internal API layer consumed by both our frontend and external integrations, and an MCP server that delivers our computed content to AI agents.

Key cross-functional interactions include coordinating with the transpiler team on data model and task orchestration, working with the DevOps and infrastructure team on distributed deployment and job execution, and collaborating with the frontend and product team on APIs and customer-facing MCP interfaces.

Key Responsibilities

  • Core backend work:
    • 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.

Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field.

Experience: Minimum 3 — 5 years as a backend engineer. 7+ years experience preferred.

Required Technical Skills

  • 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.

Preferred and Nice-to-Have Technical Skills

  • 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.

Why Join Driver

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.

Benefits

  • 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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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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