AI-Native Builder

About Faros

Software engineering is undergoing the largest transformation in its history.

As organizations invest heavily in AI for software development, they’re facing a new set of questions:
Where is AI actually being used? What impact is it having? Which investments are creating value? Where are teams getting stuck? And how do humans and AI work together effectively at scale?

Faros helps organizations answer those questions.

We sit at the center of the engineering operating system, connecting data across code, pull requests, deployments, work tracking systems, developer workflows, and AI tools. This gives us a uniquely rich view into how software is being built, how AI is being adopted, and what outcomes organizations are actually getting from those investments.

That same operational context is also what makes AI effective in large, complex enterprises. AI performs best when it understands the systems, people, processes, codebases, and business context surrounding a decision. Faros helps create and organize that context, enabling AI systems to operate with greater accuracy, relevance, and trust in environments that are often fragmented, messy, and difficult to navigate.

We believe the next generation of engineering organizations will be powered by a combination of human judgment, AI capabilities, and rich operational context. Faros is building the foundation that helps all three work together.

Our customers include some of the world’s most sophisticated engineering organizations, including Autodesk, Discord, Coursera, and others.

We are looking for AI‑Native Builders.

This is not a traditional software engineering role. We are not looking for people who simply use AI tools. We are looking for builders who understand that the scarce resource is no longer code — it is judgment.

As an AI‑Native Builder, you will identify opportunities, rapidly test ideas, build products, automate workflows, create capabilities, design evaluation systems, and help define how engineering itself evolves in the age of AI.

You may build software products, internal platforms, agent workflows, evaluation frameworks, data systems, automation pipelines, prototypes, or entirely new capabilities that do not yet fit into a traditional organizational chart.

Success in this role is measured by outcomes, learning velocity, and leverage — not by lines of code written.

You will:

• Build the intelligence layer that helps engineering organizations understand how work happens across people, code, systems, and AI
• Create agents and workflows that use Faros’s operational context to assist with engineering planning, delivery, review, quality, reliability, and decision‑making
• Design the context systems, memory, tooling, and retrieval capabilities that allow AI to operate accurately within the messy realities of enterprise software development
• Build evaluation frameworks that measure the effectiveness of humans, AI, and human‑AI systems against real engineering outcomes
• Develop reusable platform capabilities that make it easier for customers to build, deploy, govern, and improve AI‑powered engineering workflows
• Rapidly experiment with emerging models, tools, and techniques, turning promising ideas into customer‑facing capabilities
• Use data and evidence to identify bottlenecks in software delivery and create products that help organizations continuously improve
• Help define what great engineering looks like in a world where humans and AI build software together

Outcomes over activity The goal is not token maxxing. The goal is not more lines of code, more prompts, or more pull requests. The goal is creating value.

Leverage over labor As the cost of execution falls, the ability to create leverage becomes increasingly valuable. AI‑native builders create systems, workflows, context, automation, and capabilities that amplify the output of people, teams, and agents.

Learning velocity over existing expertise The half‑life of knowledge continues to shrink. The people who thrive won’t necessarily be those who know the most today, but those who can learn, adapt, and reconfigure themselves the fastest as the landscape changes.

Experiments over…