What You Will Do:
- Define and drive the technical vision, roadmap, and strategy for Fortinet's Data Platform's GenAI components, enabling scalable development and deployment of AI applications powered by LLMs and agentic workflows
- Guide the design and development of platform capabilities such as agent orchestration, RAG integration, LLM model configuration, prompt tooling, and fine-tuning pipelines
- Drive efforts around LLM inference optimization, including caching, prompt tuning, and latency improvements, ensuring efficient and cost-effective model usage across applications
- Collaborate with engineering, product, and operations teams to ensure effective adoption of GenAI capabilities in high-impact workflows
- Partner with stakeholders to build reusable AI agents that enhance productivity, automate reasoning tasks, and integrate securely with internal systems and tools
- Mentor new hires and fellow engineers, fostering growth in technical depth and platform mindset
- Establish best practices and processes that ensure engineering excellence, operational sustainability, and a seamless developer experience
- Develop high quality, secure, scalable enterprise-grade backend components based on technical requirements specifications and design artefacts within expected time and budget
- Follow standard practices to develop and maintain AI systems along with compliance
We Are Looking for:
- 8+ years of experience in AI/ML engineering, GenAI, data science, or related roles.
- 3+ years of experience as a technical lead, guiding teams through complex design decisions and setting high benchmarks for code quality, performance, and scalability
- 3+ years of Data Engineering with data cleaning, enrichment and data mapping.
- Proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Ollama, XGBoost, Hugging Face), vLLM, LM Studio, GPT4All
- Experience with modern GenAI frameworks and libraries (e.g., LangChain, LlamaIndex, Hugging Face Transformers).
- Familiarity with best practices for responsible AI, including data privacy, bias mitigation, compliance and model monitoring.
- Proven experience in fine-tuning and customizing foundation models to improve task-specific performance and domain alignment
- Deep knowledge of LLM inference optimization techniques, including prompt tuning, caching, quantization, and latency reduction across different model families
- Strong programming skills in Python (must) and similar languages, with an emphasis on AI/ML systems development and platform engineering
- Demonstrated ability to work cross-functionally and influence product development through a combination of technical leadership and user-centered thinking
- Passion for operational excellence, automation, and delivering scalable, developer-friendly AI infrastructure
Desired Experience: 10+ years in Software Engineering and 3+ years in AI/ML space.
Working Conditions: This position requires working from the office full-time remote work is not available.
About Product/Team: FortiRecon is Fortinet's threat exposure management solution. It helps enterprises move from reactive to a proactive, programmatic, and framework-based approach to exposure management and vulnerability assessment
