Staff Engineer: Agentic AI for Desktop Engineering

Wwshemi; San Francisco (CA); Presencial; USD 160.000 - 250.000; Jornada completa

Descripción de la vacante

Wwshemi in San Francisco, CA, seeks a hands-on Tech Lead to drive the development of intelligent agents for desktop engineering workflows. You will shape architecture, connect user research with product priorities, and improve reliability and cost efficiency of real-world tasks.

The role combines leadership and hands-on coding on a small AI team, with a focus on tool calling, context management, and robust evaluations to ensure agent success in engineering software environments.

Formación

• 7+ years software engineering with hands-on AI experience.
• Proven ability to ship LLM-based agents that perform real-world actions.
• Strong Python skills and familiarity with tooling for evaluation.

Responsabilidades

• Own task success metrics and improve completion rates for agent workflows.
• Build evaluation infrastructure based on user stories and workflows.
• Set budgets and track costs for completed tasks and workflows.
• Collaborate with researchers and engineers to map and validate workflows.
• Translate stories into testable evaluations and prioritize coverage by value.
• Make architecture decisions for tool calling, state management, and routing.
• Provide technical direction, review designs, and contribute production code.
• Align agent behavior with product needs and customer workflows.

Conocimientos

LLM architecture

Python

Code review

Leadership

Evaluation tooling

Herramientas

LLM Tooling

Python tooling

Observability

Tracing

Tool APIs

Descripción del empleo

Wwshemi in San Francisco, CA, seeks a hands-on Tech Lead to drive the development of intelligent agents for desktop engineering workflows. You will shape architecture, connect user research with product priorities, and improve reliability and cost efficiency of real-world tasks.

The role combines leadership and hands-on coding on a small AI team, with a focus on tool calling, context management, and robust evaluations to ensure agent success in engineering software environments.