Applied AI Engineer (Internship) at Fortinet in Santa Clara, CA

Summary: Fortinet is a cybersecurity company building a next-generation AI-driven operations platform. They are looking for an Applied AI Engineer Intern who can architect, build, and scale secure, performant systems while collaborating closely with product, AI/ML, and design teams. Responsibilities: - Architect and implement scalable AI agent and backend systems for high-volume, real-time operational workloads - Integrate LLMs and GenAI components into production workflows, including fine-tuning, prompt orchestration, retrieval pipelines, and evaluation loops - Design and implement robust data flows (e.g., event streams, message queues, job orchestration) to support next-gen SOC/NOC capabilities - Define clear contracts between AI services, backend APIs, and frontend clients - Contribute to trustworthy AI delivery: streaming responses with structured outputs, redaction/guardrails, and human-in-the-loop review - Partner with backend team to build data pipeline - Collaborate with design and frontend engineers to translate complex backend/AI systems into intuitive UIs - Lead technical reviews, and help shape coding standards and architectural patterns - Communicate clearly with both technical and non-technical stakeholders about trade-offs, performance, and reliability Required Qualifications: - Proven track record shipping data-intensive and AI-enhanced applications - Proficiency with at least one modern backend runtime/language (e.g., Python, Go) and associated frameworks - Strong background in designing APIs (REST/WebSocket/GraphQL) and integrating with real-time/event-driven systems - Deep understanding of databases and storage paradigms (e.g., Postgres, graph DBs, time-series stores) - Experience with authentication/authorization, session management, and enterprise integrations - Familiarity with distributed systems, scalability, and observability best practices - Hands-on experience building or integrating AI systems in production - Familiarity with multi-agent, retrieval-augmented generation (RAG), prompt engineering, evaluation, and guardrails - Exposure to model fine-tuning workflows or orchestration frameworks for multi-tool AI agents - Strong problem-solving skills and attention to detail - Excellent written and verbal communication - Comfortable operating in fast-moving, ambiguous contexts - Experience working with distributed teams Required Skills: Python, API design, AI system integration Important Skills: Databases, Distributed systems Benefits: Opportunity to shape the future of AI-assisted cybersecurity and operations at scale., End-to-end ownership of high-impact product surfaces used daily by enterprise customers., Collaborative environment with experienced engineers, researchers, and designers., Continuous learning in AI/ML, distributed systems, and modern web technologies., Terrific benefits and competitive compensation.