Software Development Engineer

Fortinet, Inc.; Sunnyvale (CA); On-site; USD 160,000 - 200,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Paid holidays

Vacation time

Sick time

Comprehensive leave program

Job summary

A leading cybersecurity firm is seeking a candidate to enhance LLM security by architecting monitoring and filtering systems. This role requires expertise in deploying AI systems, managing prompts, and safeguarding against emerging threats. The ideal candidate will have strong skills in application security and experience in microservices architecture. A competitive salary range is available, along with robust employee benefits including medical insurance and a 401(k) plan.

Qualifications

• Hands‑on experience with AI/ML systems, particularly LLMs and prompt handling.
• Solid knowledge of application security and building secure systems.
• Experience designing microservices and using containerization and orchestration.
• Ability to design clean and secure APIs with performance optimization.
• Familiarity with data protection best practices and responsible AI principles.
• Understanding of emerging AI security guidelines and implementation.
• Experience with RAG architectures, vector databases, and monitoring workflows.
• Strong programming skills in Python and C/C++.

Responsibilities

• Architect and implement functions to monitor LLM requests/responses.
• Build a scalable pipeline for high-volume LLM traffic.
• Develop monitoring systems to detect anomalies in LLM usage.
• Collaborate on security requirements and mentor junior engineers.
• Ensure timely delivery of high-quality software features.
• Communicate effectively with technical and non-technical stakeholders.

Skills

Large language models deployment

Application security principles

Microservices architecture design

API design

Data protection and privacy

AI security guidelines

Retrieval-augmented generation (RAG)

Programming skills in Python

Familiarity with PyTorch or TensorFlow

Tools

Docker

Kubernetes

AWS

GCP

Azure

Hugging Face Transformers

Job description

Job Responsibilities:

1. Architect and implement functions to monitor and filter LLM requests/responses in real time, preventing prompt injection attacks and unauthorized data leakage.
2. Build a highly scalable pipeline capable of handling high-volume LLM traffic with low latency, including optimizing databases and caching for quick threat detection and response.
3. Develop monitoring, logging, and alerting systems to detect anomalies in LLM usage (e.g. suspicious spikes indicating denial-of-service attacks or unusual prompt patterns indicating misuse).
4. Collaborate with teams to translate security requirements into platform features. Mentor junior engineers on secure backend development and best practices in an Agile environment.
5. Ensure the timely delivery of high-quality software features while adhering to project schedules.
6. Communicate effectively across teams, with both technical and non-technical stakeholders, in both verbal and written forms.

Job requirements:

1. Hands‑on experience with deploying or integrating large language models or other AI/ML systems (e.g. implementing model inference pipelines, fine‑tuning models, or working with LLM APIs and prompt handling). Strong understanding of how prompts and context are managed in LLM applications.
2. Solid knowledge of application security principles and experience building secure systems. Familiarity with AI‑specific threats (prompt injection, data poisoning, output manipulation) and a keen interest in staying ahead of new generative AI attack vectors.
3. Proven experience designing microservices architectures and using containerization (Docker) and orchestration (Kubernetes). Comfortable with cloud platforms (AWS, GCP, or Azure) and designing observable, resilient services in a production environment.
4. Ability to design clean, efficient, and secure APIs. Strong understanding of network protocols, data caching, and performance optimization.
5. Knowledge of data protection and privacy best practices – able to design systems that handle sensitive data responsibly and comply with regulations. Understanding of responsible AI principles (ethics, bias, transparency) and how they relate to secure AI system design.
6. Familiarity with emerging AI security guidelines such as OWASP’s Top 10 for LLMs/Generative AI Security (e.g. knowledge of prompt injection, insecure output handling, data poisoning risks) and experience implementing related mitigations.
7. Experience with retrieval‑augmented generation (RAG) architectures, vector databases/embedding stores, or streaming data pipelines for ML – especially as they relate to monitoring and securing LLM workflows (helps in addressing vector embedding attack vulnerabilities).
8. Understanding of responsible AI and techniques for detecting AI‑generated misinformation or hallucinations. Experience building or integrating content filtering, policy enforcement, or fact‑checking systems in AI applications is a plus.
9. Strong programming and debugging skills, particularly in Python and C/C++.
10. Familiarity with Frameworks like PyTorch or TensorFlow for model integration; libraries such as Hugging Face Transformers or LangChain for LLM and prompt management; LLM APIs (OpenAI, etc.) and vector databases is beneficial.

The US base salary range for this full‑time position is $160,000-$200,000. Fortinet offers employees a variety of benefits, including medical, dental, vision, life and disability insurance, 401(k), 11 paid holidays, vacation time, and sick time as well as a comprehensive leave program.

Wage ranges are based on various factors including the labor market, job type, and job level. Exact salary offers will be determined by factors such as the candidate's subject knowledge, skill level, qualifications, experience, and geographic location.

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

Why Join Us:
We encourage candidates from all backgrounds and identities to apply. We offer a supportive work environment and a competitive Total Rewards package to support you with your overall health and financial well‑being. Embark on a challenging, enjoyable, and rewarding career journey with Fortinet. Join us in bringing solutions that make a meaningful and lasting impact to our 660,000+ customers around the globe.