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