AI Agent Systems QA Engineer

Fortinet Inc.; Santa Clara (CA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Health insurance

401(k)

Paid holidays

Equity program

Job summary

Fortinet Inc. is seeking an early-career engineer to help build AI agents for improving the efficiency of network security product development. The role targets candidates with 0–2 years of experience and recent graduates.

You will design scalable multi-agent systems, support RAG pipelines with vector databases, integrate tools via APIs, and evaluate LLMs to enhance reliability. A strong Python background and cloud/container familiarity are valued.

Qualifications

• Bachelor's degree in CS, AI, ML, or a related technical field.
• Strong project-based experience with generative AI is a plus.
• Familiarity with AI agent frameworks.
• Basic understanding of LLMs, prompt engineering, and generative AI concepts.
• Some exposure to vector databases, retrieval systems, or RAG architectures.
• Familiarity with major LLM models.
• Basic familiarity with cloud platforms (AWS, GCP, Azure) and containers (Docker).
• Solid Python skills and good understanding of software engineering fundamentals.
• Motivated, curious, and excited to learn.

Responsibilities

• Design and implement resilient, scalable multi-agent systems and agentic AI.
• Support RAG pipelines, including vector databases and hybrid search
• Integrate agents with external tools, APIs, and business systems
• Run LLM/RAG evaluations to identify issues and improve reliability
• Write prompts and support light model fine-tuning

Skills

Python

AI agent frameworks

Prompt engineering

LLMs concepts

Cloud platforms

Software engineering fundamentals

Education

Bachelor's degree in CS/AI/ML

Tools

Docker

Vector databases

Job description

Fortinet Inc. is seeking an early-career engineer to help build AI agents for improving the efficiency of network security product development. The role targets candidates with 0–2 years of experience and recent graduates.

You will design scalable multi-agent systems, support RAG pipelines with vector databases, integrate tools via APIs, and evaluate LLMs to enhance reliability. A strong Python background and cloud/container familiarity are valued.