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