Applied AI Engineer
About The Position
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. Role Overview 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.
Requirements
- 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.
Nice To Haves
- 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.
Responsibilities
- 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.
Benefits
- 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.
- Competitive salary and meaningful equity
- Comprehensive health, dental and vision coverage
- Fast-paced environment with flexibility and ownership
- Real impact, zero bureaucracy
- A front-row seat to building category-defining AI infrastructure
- flexible work hours
- a collaborative culture focused on learning and impact
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
