Principal Software Engineer

Gradial•Seattle, WA

10d•$160,000 - $250,000

About The Position

Gradial is seeking a Principal Software Engineer to drive the architecture and technical vision behind AI-native systems that transform how creative teams build and update websites. As a foundational technical leader, you’ll push the boundaries of how LLMs can power real-world workflows and reimagine the intersection of language, software, and creativity. You’ll work closely with engineering, product, and design leaders to shape not just features, but the technical backbone and strategic direction of the company. This is a rare opportunity to set the blueprint for a fast-evolving product in a high-agency, low-ego environment committed to solving hard problems from first principles.

Requirements

8+ years of professional software engineering experience, including significant leadership of complex technical initiatives.
Deep expertise in distributed systems, algorithms, and scalable software design.
Proven track record architecting and shipping systems in fast-moving, high-ambiguity environments.
Hands-on experience with LLM integration, generative AI frameworks, or building AI-native applications.
Strong communication and cross-functional leadership skills, with the ability to influence technical and non-technical audiences.
High-agency, ownership-driven mindset with a passion for solving real-world problems at scale.
Background in technical fields such as computer science, mathematics, physics, or systems engineering.

Nice To Haves

Experience building or scaling AI agent architectures for production environments.
Prior experience in early-stage startups where you owned both strategy and execution.
Passion for designing systems that blend technical sophistication with elegant, intuitive user experiences.

Responsibilities

Define and drive the technical architecture for systems that convert natural language into intelligent, multi-step workflows using generative AI.
Lead the design, implementation, and scaling of LLM agents for real-time inference, dynamic prompting, memory management, and tool orchestration.
Set engineering standards and influence system design across the stack, with a focus on performance, reliability, and long-term extensibility.
Design learning systems that integrate customer feedback, usage data, and brand preferences to evolve autonomously over time.
Mentor senior engineers, fostering a culture of technical excellence, rapid iteration, and ownership.
Collaborate deeply with product and design leaders to rethink how interfaces and features dynamically adapt to user intent.
Champion best practices in testing, observability, deployment, and operational excellence to ensure system health at scale.
Own critical, ambiguous problem spaces from end to end, advocating for technical and product innovation.