Fortinet

Staff AI Agent Engineer

Sunnyvale, CA
USD 180k - 260k
Python Go API REST GraphQL PostgreSQL JavaScript TypeScript React LLM GenAI Machine Learning AI
Description

Staff Engineer - AI Agent

Location: Sunnyvale, CA, United States

We are a cybersecurity company building a next-generation AI-driven operations platform, designed to power complex, high-stakes workflows. Our product integrates generative AI deeply into real-time operational environments—combining reasoning, retrieval, and automation into scalable, trustworthy systems.

1. ABOUT THE ROLE

We’re a cybersecurity company building a next-generation AI-driven operations platform, designed to power complex, high-stakes workflows. The product integrates generative AI deeply into real-time operational environments—combining reasoning, retrieval, and automation into scalable, trustworthy systems.

We’re looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You’ll work closely with product, AI/ML, and design teams to deliver capabilities that drive investigation speed, streamline operations, and unlock new modes of human-AI collaboration.

 

2. KEY RESPONSIBILITIES

2.1 Development

  • End-to-end ownership of complex system features: from backend services and API design to user-facing interactions.

  • 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.

  • Build resilient real-time user experiences (e.g., dashboards, streaming data visualization, multi-user collaboration).

  • 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.

2.2 Collaboration

  • Partner with AI/ML engineers to productionize models, optimize inference pipelines, and collect feedback signals for iterative improvement.

  • 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.

 

3. REQUIRED QUALIFICATIONS

3.1 Experience

  • Proven track record shipping data-intensive and AI-enhanced applications at scale.

  • Experience owning features from system architecture through production delivery.

  • BS: 5+ years in backend or full-stack systems for high-availability, security-sensitive environments OR

  • MS: 3+ years in the same OR

  • PhD: 0+ year in the same

3.2 Technical Skills

Core Backend & Platform (Must Have)

  • 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.

AI/ML Integration (StronglApplied AI Engineer - AI Agent

1. ABOUT THE ROLE

We’re a cybersecurity company building a next-generation AI-driven operations platform, designed to power complex, high-stakes workflows. The product integrates generative AI deeply into real-time operational environments—combining reasoning, retrieval, and automation into scalable, trustworthy systems.

We’re looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You’ll work closely with product, AI/ML, and design teams to deliver capabilities that drive investigation speed, streamline operations, and unlock new modes of human-AI collaboration.

 

2. KEY RESPONSIBILITIES

2.1 Development

  • End-to-end ownership of complex system features: from backend services and API design to user-facing interactions.

  • 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.

  • Build resilient real-time user experiences (e.g., dashboards, streaming data visualization, multi-user collaboration).

  • 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.

2.2 Collaboration

  • Partner with AI/ML engineers to productionize models, optimize inference pipelines, and collect feedback signals for iterative improvement.

  • 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.

 

3. REQUIRED QUALIFICATIONS

3.1 Experience

  • Proven track record shipping data-intensive and AI-enhanced applications at scale.

  • Experience owning features from system architecture through production delivery.

  • BS: 5+ years in backend or full-stack systems for high-availability, security-sensitive environments OR

  • MS: 3+ years in the same OR

  • PhD: 0+ year in the same

3.2 Technical Skills

Core Backend & Platform (Must Have)

  • 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.

AI/ML Integration (Strongly Desired)

  • 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.

Frontend (Nice-to-Have)

  • Solid proficiency with modern JavaScript/TypeScript and a component-based framework (React or equivalent).

  • Experience building data-heavy dashboards and visualization for real-time operations.

  • Understanding of streaming UX patterns (WebSocket/SSE) and responsive design systems.

Communication & Soft Skills

  • 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.

 

4. PREFERRED QUALIFICATIONS (BONUS POINTS)

  • Experience with event-driven architectures, message queues, and background job orchestration.

  • Exposure to graph/time-series data modeling and visualization.

  • Knowledge of real-time collaboration systems (presence, concurrency control).

  • Familiarity with SOC/NOC operations workflows, incident management, and observability pipelines.

  • Contributions to open-source AI/ML tools or backend frameworks.

 

WHAT WE OFFER

  • 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.

  • Flexible work arrangements and competitive compensation.y Desired)

  • 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.

Frontend (Nice-to-Have)

  • Solid proficiency with modern JavaScript/TypeScript and a component-based framework (React or equivalent).

  • Experience building data-heavy dashboards and visualization for real-time operations.

  • Understanding of streaming UX patterns (WebSocket/SSE) and responsive design systems.

Communication & Soft Skills

  • 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.

 

4. PREFERRED QUALIFICATIONS (BONUS POINTS)

  • Experience with event-driven architectures, message queues, and background job orchestration.

  • Exposure to graph/time-series data modeling and visualization.

  • Knowledge of real-time collaboration systems (presence, concurrency control).

  • Familiarity with SOC/NOC operations workflows, incident management, and observability pipelines.

  • Contributions to open-source AI/ML tools or backend frameworks.

 

WHAT WE OFFER

  • 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.

  • Flexible work arrangements and competitive compensation.

     

Must be authorized to work in the U.S. without sponsorship.

The US base salary range for this full-time position is $179,500–$260,000. Exact salary offers will be determined by factors such as research focus, publication record, skill level, qualifications, and geographic location.

All roles are eligible to participate in the Fortinet equity program. Bonus eligibility is reviewed at the time of hire and annually at the company’s discretion.

About Us

Fortinet (NASDAQ: FTNT) secures the largest enterprise, service provider, and government organizations around the world. Fortinet empowers its customers with intelligent, seamless protection across the expanding attack surface and the power to take on ever-increasing performance requirements of the borderless network - today and into the future. Only the Fortinet Security Fabric architecture can deliver security without compromise to address the most critical security challenges, whether in networked, application, cloud or mobile environments. Fortinet ranks number one in the most security appliances shipped worldwide and more than 500,000 customers trust Fortinet to protect their businesses.

We are committed to providing reasonable accommodations for all qualified individuals with disabilities. If you require assistance or accommodation due to a disability, please contact us at [email protected].
 
Fortinet is an equal opportunity employer. We value diversity in our company, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, military/veteran status or any other applicable legally protected characteristics in the location in which the candidate is applying.
We’re a cybersecurity company building a next-generation AI-driven operations platform, designed to power complex, high-stakes workflows. The product integrates generative AI deeply into real-time operational environments—combining reasoning, retrieval, and automation into scalable, trustworthy systems.
Fortinet
Fortinet

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