AI Workflows – Safety Decision Making Intern

Zoox

. Develop, prototype, and implement agentic workflows and AI-assisted tools that automate complex safety evaluations and triage operational signals .

Posted 11/7/2026internshipFoster City • California • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and deploying AI tools and workflows, with a strong foundation in Python and object-oriented programming. Capable of applying AI/ML techniques to safety analytics and risk management while ensuring reliability and safety in decision-making contexts.

Highest-signal resume keywords

Python ProgrammingAI Tool DevelopmentLLM APIsSafety AnalyticsDatabase Architecture

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Object-Oriented ProgrammingAI/ML TechniquesPrototypingAPI DevelopmentEvaluation Harness Design

Soft Skills

Analytical Problem-SolvingTechnical Communication

Tools & Technologies

LangChainLlamaIndexClaude/CursorStreamlitFastAPIFlask

Industry Keywords

Safety EvaluationsRisk ReportingGenerative AIOperational SignalsData Warehousing

Tech Stack

Tools & technologies

FlaskNoSQLPythonSQL

About the role

Key responsibilities & impact

Develop, prototype, and implement agentic workflows and AI-assisted tools that automate complex safety evaluations and triage operational signals
Characterize the capabilities, edge cases, and failure modes of LLMs and AI workflows to ensure decision aids operate within safety-critical reliability thresholds
Connect generative AI agents to structured safety databases and operational logs to automate real-time synthesis and risk reporting
Collaborate with safety strategists and software engineers to test prototypes in real operational scenarios and iterate based on user feedback
Develop and deploy internal AI tools and agentic workflows that empower safety operators and analysts to make faster, more consistent, and data-driven safety decisions

Requirements

What you’ll need

Currently pursuing a Master’s degree (or advanced degree) in Computer Science, Artificial Intelligence, Robotics, Data Science, or related engineering field
Good academic standing and enrolled at an accredited college or university throughout the internship
Expected graduation date between Fall 2027 and Summer 2028
Able to commit to a full-time, 12-week internship
Ability to relocate to the Bay Area, California, for the duration of the internship
Interns at Zoox may not use proprietary information for thesis or publication outside of Zoox
Strong software engineering fundamentals in Python and object-oriented programming
Hands-on experience developing and deploying AI tools, LLM APIs, and agentic workflows (e.g., LangChain, LlamaIndex, Claude/Cursor environments)
Critical understanding of the limitations, hallucinations, and verification methods required when deploying AI in decision-making contexts
Experience building working prototypes, APIs, or internal web dashboards (e.g., Streamlit, FastAPI, or Flask)
Strong analytical problem-solving and clear written/verbal technical communication
Prior experience applying AI/ML techniques to autonomous systems, safety analytics, or risk management
Experience designing evaluation harnesses to benchmark generative AI and prompt performance
Familiarity with database architectures (SQL/NoSQL) and data warehousing platforms

Benefits

Comp & perks

Hands-on experience with cutting-edge technology
Mentorship from some of the industry's brightest minds
Opportunity to make meaningful contributions to real projects
Full-time, 12-week internship