Principal Architect, AI-Driven Cloud Platform

Code and Theory, LLC; Austin (TX); On-site; USD 200,000 - 260,000; Full time

Job summary

Code and Theory, LLC is seeking a Principal Engineer to lead architecture and technical direction while guiding a matrixed team of DevOps, infrastructure, and data professionals. You will set architectural vision, raise engineering quality, and drive how AI reshapes software delivery.

You will lead engineers across cloud, backend, and data domains, shaping patterns and standards, and advancing AI-enabled tooling and workflows to improve velocity and reliability.

Qualifications

• Deep expertise in cloud architecture and multi-cloud patterns.
• Strong backend engineering track record and production systems experience.
• Broad data engineering knowledge across ingestion, transformation, warehousing.
• DevOps mindset focused on quality, efficiency, and AI-driven workflows.
• Experience leading engineers in matrixed or cross-functional structures.
• Familiarity with AI-enabled development tools, automation, and evaluation.
• Experience orchestrating AI-driven workflows and model/tool selection.

Responsibilities

• Manage one or more pods of engineers building our flagship product.
• Lead cloud architecture across the organization, enabling multi-cloud environments.
• Direct DevOps strategy with focus on AI-powered production workflows.
• Shape backend architecture and development standards.
• Evolve data engineering practices to keep data infrastructure reliable and scalable.

Skills

Cloud architecture

Backend development

Data engineering

DevOps mindset

Leadership experience

AI-enabled development

Multi-cloud design

Tools

AWS

GCP

Azure

CI/CD tooling

Job description

Code and Theory, LLC is seeking a Principal Engineer to lead architecture and technical direction while guiding a matrixed team of DevOps, infrastructure, and data professionals. You will set architectural vision, raise engineering quality, and drive how AI reshapes software delivery.

You will lead engineers across cloud, backend, and data domains, shaping patterns and standards, and advancing AI-enabled tooling and workflows to improve velocity and reliability.