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 workflowsGuide the design and development of platform capabilities such as agent orchestration, RAG integration, LLM model configuration, prompt tooling, and fine-tuning pipelinesDrive efforts around LLM inference optimization, including caching, prompt tuning, and latency improvements, ensuring efficient and cost-effective model usage across applicationsCollaborate with engineering, product, and operations teams to ensure effective adoption of GenAI capabilities in high-impact workflowsPartner with stakeholders to build reusable AI agents that enhance productivity, automate reasoning tasks, and integrate securely with internal systems and toolsMentor new hires and fellow engineers, fostering growth in technical depth and platform mindsetEstablish best practices and processes that ensure engineering excellence, operational sustainability, and a seamless developer experienceDevelop 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 scalability3+ 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, GPT4AllExperience 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 alignmentDeep knowledge of LLM inference optimization techniques, including prompt tuning, caching, quantization, and latency reduction across different model familiesStrong programming skills in Python (must) and similar languages, with an emphasis on AI/ML systems development and platform engineeringDemonstrated ability to work cross-functionally and influence product development through a combination of technical leadership and user-centered thinkingPassion 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