AI-Native Builder

About the role

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.

Responsibilities

• 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

Qualifications

• Strong software engineering fundamentals
• A history of building products, systems, tools, automation, workflows, or side projects
• Demonstrated ability to learn new technologies quickly and independently
• Experience using AI to accelerate development, research, analysis, or decision-making
• Strong problem-solving skills and comfort operating in ambiguous environments
• Ability to rapidly move from idea to implementation
• Evidence of curiosity, initiative, and self-directed learning
• Excellent written and verbal communication skills
• Strong judgment and an ability to reason through tradeoffs
• A bias toward action and experimentation

What We Value

• Outcomes over activity
• Leverage over labor
• Learning velocity over existing expertise
• Experiments over opinions
• Capabilities over interfaces
• Systems over silos
• Human judgment over human execution

Required Qualifications

• Strong software engineering fundamentals
• A history of building products, systems, tools, automation, workflows, or side projects
• Demonstrated ability to learn new technologies quickly and independently
• Experience using AI to accelerate development, research, analysis, or decision-making
• Strong problem-solving skills and comfort operating in ambiguous environments
• Ability to rapidly move from idea to implementation
• Evidence of curiosity, initiative, and self-directed learning
• Excellent written and verbal communication skills
• Strong judgment and an ability to reason through tradeoffs
• A bias toward action and experimentation

Preferred Qualifications

• Built systems, platforms, tools, or workflows adopted by teams or organizations
• Designed AI agents, agentic workflows, evaluation frameworks, or AI-powered products
• Built automation that significantly improved organizational productivity
• Open-source contributions, hackathon projects, startups, research projects, or other evidence of self-directed building
• Deep experimentation with modern AI models, agents, developer tools, or emerging technologies
• Experience navigating major technology shifts and helping others adapt
• A track record of identifying important opportunities before they become obvious

Compensation Range

$200K - $250K