Applied AI Engineer – AI Agent

Fortinet

Applied AI Engineer building AI-integrated features for real-time operational workloads at a cybersecurity company. Collaborating with engineers and researchers to enhance human-AI collaboration.

Posted 5/26/2026full-timeSunnyvale • California • 🇺🇸 United StatesEntry Level💰 $123,000 - $151,000 per yearWebsite

Tech Stack

Tools & technologies

Distributed SystemsGoGraphQLPostgresPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Build and maintain backend services and AI-integrated features for real-time, high-volume operational workloads
Integrate LLMs and GenAI components into production workflows, including prompt orchestration, retrieval pipelines, and evaluation loops
Help design data flows (event streams, message queues, job orchestration) to support next-generation SOC/NOC capabilities
Write clean, well-documented code with clear API contracts between AI services, backend APIs, and frontend clients
Contribute to trustworthy AI delivery: streaming responses, structured outputs, redaction/guardrails, and human-in-the-loop review
Work with senior backend engineers to build data pipelines that power AI-driven features
Collaborate with design and frontend engineers to translate complex backend/AI systems into intuitive user experiences
Participate in code reviews, technical design discussions, and team retrospectives
Communicate clearly with both technical and non-technical teammates about progress, blockers, and trade-offs

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Computer Engineering, AI/ML, or a closely related technical field (graduated within the past 6 months or graduating by Summer 2026)
Proficiency in at least one modern backend language (e.g., Python, Go) demonstrated through coursework, personal projects, or internships
Familiarity with API design (REST, WebSocket, or GraphQL) and basic understanding of event-driven or real-time systems
Coursework or hands-on exposure to relational databases (e.g., Postgres) and data modeling fundamentals
Basic understanding of authentication/authorization patterns and web application security
Awareness of distributed systems concepts (load balancing, caching, message queues)
Completed coursework or projects involving machine learning, NLP, or deep learning
Familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) from class or personal projects
Interest in or exposure to LLM-based applications, prompt engineering, retrieval-augmented generation and agentic system design
Strong problem-solving skills and intellectual curiosity
Excellent written and verbal communication skills
Eagerness to learn quickly, take feedback constructively, and grow in a team environment
Experience working on team-based projects (class projects, hackathons, clubs, or open-source contributions)

Benefits

Comp & perks

Comprehensive benefits including medical, dental, vision, life and disability insurance
401(k)
11 paid holidays
Vacation time
Sick time

ATS Keywords

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Hard Skills & Tools

PythonGoAPI designRESTWebSocketGraphQLPostgresmachine learningNLPdeep learning

Soft Skills

problem-solvingintellectual curiositywritten communicationverbal communicationeagerness to learnfeedback receptivenessteam collaboration