Principal Software Development Engineer
Fortinet · Pune, India · Software Development
principal
Software Engineer
tech_leadership
8+ yrs
· Posted Feb 23, 2026
Skills
About this role
Fortinet is hiring a principal-level Software Engineer based in Pune, India. The posting calls out experience with Python, TensorFlow, PyTorch, scikit-learn and roughly 8+ years of relevant work.
- Role
- Software Engineer
- Function
- software engineering
- Level
- principal
- Track
- Tech leadership
- Employment
- Full-time
- Location
- Pune, India
- Work mode
- On-site
- Experience
- 8+ years
- Department
- Software Development
- Posted
- Feb 23, 2026
AI Summary
Principal-level engineer defining technical vision and strategy for Fortinet's GenAI Data Platform. Design and optimize LLM inference, agent orchestration, and RAG integration. Mentor teams and establish best practices for scalable, secure AI systems.
Job description
from Fortinet careers
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
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