Senior Applied AI Engineer

About the company Our client is a fast-growing software company. The role Raydar is recruiting for this role on behalf of our client. Design and build the core software that lets large language models carry out multi-step work reliably in production. You will shape how models are prompted and combined with conventional code, measure quality through rigorous testing, and diagnose real-world failures to make systems more robust. What you'll do - Develop the core execution framework for AI agents, including orchestration loops, tool usage and context handling. - Run experiments with models and iterate on agent behavior across realistic, long-running workflows. - Define where model decisions end and deterministic, type-checked code begins. - Build evaluation suites on realistic test environments that are dependable enough to gate releases. - Analyze production failures and trace each one to the right layer, then deliver systematic fixes. - Extend browser and computer-use agents to systems that lack APIs, with strong safety, security and auditability guarantees. - Create feedback loops and data systems that bring higher-quality real-task data into evaluation and training. Requirements What we're looking for - Experience with agent frameworks or LLM systems that use tools. - Strong Python or TypeScript skills and comfort with modern AI tooling. - Hands-on background measuring or improving model quality, whether through testing, tuning or crafting instructions for models. - Ability to own systems end to end and debug across the whole stack. - A systems mindset focused on user outcomes as well as model metrics. - Satisfaction in tracking down unpredictable production problems and converting what you learn into lasting fixes. - At least 4 years of relevant experience. - Ability to work in person five days a week at a startup pace. Bonus points - Experience building computer-use or browser-automation agents. - Familiarity with virtualization and sandboxed execution environments, including scaling them. - AI research experience with publications at leading conferences. - Experience delivering systems where correctness must hold through partial failure, such as idempotency and resumability. - Experience integrating enterprise SaaS APIs. - Comfort working with sizable, unstructured data sources such as application logs. - Early-stage engineering experience that included working directly with customers. Benefits Compensation and benefits - Base salary: USD 200,000 to 300,000 per year - Health insurance - Unlimited paid time off Location and work model - San Francisco, CA, United States - On-site, five days a week in office - Full-time