Applied AI Engineer

Gradial is a Seattle-based startup enabling digital experiences at the speed of thought. We empower marketers and creatives to implement their ideas directly, with software that adapts over time. Our platform automates website and design system updates, large-scale migrations to new design systems, and continuous content optimization while adhering to company and product brands.

Backed by world class investors, we’re looking to scale our platform and expand our team. At Gradial, we operate with extreme ownership, bias towards action and critical path planning. We tackle problems from first principles, question assumptions, and find creative solutions. If you want to take risks, work on groundbreaking technology, and see the direct impact of your work, Gradial is where you belong.

We’re looking for an Applied AI Engineer to help build the next generation of agentic systems. This role combines deep software engineering skills with an experimental mindset around how AI can be practically applied to solve real user problems.

You’ll collaborate across product, research, and engineering to design agents that reason, interact with environments and evolve through feedback. Ideal candidates bring curiosity, a love of ambiguous problems, and hands‑on experience applying LLMs in production.

• Build autonomous and semi‑autonomous agent workflows that interact with browsers, codebases, and APIs to complete complex content operations.
• Evaluate model behavior in live environments and pioneer approaches for applying reinforcement learning to end‑to‑end agent systems.
• Design modular frameworks for tools, memory, and evaluators to enable continuous learning and improvement of agents.
• Develop data pipelines to collect, transform, and annotate real‑world usage data for SFT and RL training.
• Design and build proprietary agent libraries, prompting strategies and benchmarking frameworks.
• Partner with customers and internal stakeholders to understand edge cases and align AI behaviors with user expectations.

• 4+ years of software engineering experience, with at least a year working directly on AI/ML‑powered applications.
• Strong fluency in AI tooling (e.g. OpenAI APIs, Anthropic APIs).
• Practical understanding of LLMs, prompt engineering and agentic architectures.
• Experience building production systems that integrate external environments – code execution, browser automation or API orchestration.
• High degree of ownership and comfort in experimental, fast‑moving environments.

• Familiarity with benchmarks like SWE‑bench or evaluation strategies for tool‑using agents.
• Exposure to customer‑facing roles or user research for AI product development.
• Background in reinforcement learning or data‑centric AI approaches.

The salary range for this position is $130,000 – $220,000 annually
. Final compensation will be determined based on factors such as experience, skills, and qualifications. In addition to base salary, this role may be eligible for performance‑based bonuses and equity awards. Gradial offers a comprehensive benefits package, including medical, dental & vision insurance, 401k retirement plan, paid time off, paid sick leave and other employee wellness programs.

• Learn quickly and actively seek out new challenges.
• Embrace AI as a core tool for problem‑solving, creativity and scale.
• Show a strong work ethic, high ownership and bias toward action.
• Communicate clearly, directly and with curiosity.
• Thrive in fast‑paced, hyper‑growth environments where building better > maintaining status quo.

As an AI‑first company, we prioritize AI literacy as a core competency in our hiring decisions. We’re excited by candidates who thoughtfully apply AI tools in their work, but during interviews we’re focused on you. This is your opportunity to show how you think, communicate, and solve problems. Over‑reliance on AI‑generated responses during the interview process (especially when it obscures your own voice) will result in disqualification.

We want to understand your unique perspective and how you approach challenges, both with and without AI.