Fortinet

Principal Software Development Engineer

Posted 8 Hours Ago

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Pune, Mahārāshtra, IND

In-Office

Senior level

Security • Software • Cybersecurity

The Role

Lead technical vision and roadmap for Fortinet's GenAI data platform. Design and build agent orchestration, RAG integration, LLM configuration, prompt tooling, and fine-tuning pipelines. Optimize LLM inference (caching, quantization, latency), develop secure scalable backend components, collaborate cross-functionally, mentor engineers, and drive best practices for responsible AI and operational excellence.

Summary Generated by Built In

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

Skills Required

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.
3+ years of Data Engineering experience with data cleaning, enrichment, and data mapping.
Proficiency in machine learning frameworks and libraries: TensorFlow, PyTorch, Scikit-learn, Ollama, XGBoost, Hugging Face, vLLM, LM Studio, GPT4All.
Experience with modern GenAI frameworks and libraries: LangChain, LlamaIndex, Hugging Face Transformers.
Familiarity with responsible AI best practices: data privacy, bias mitigation, compliance, and model monitoring.
Proven experience fine-tuning and customizing foundation models for task-specific performance.
Deep knowledge of LLM inference optimization techniques (prompt tuning, caching, quantization, latency reduction).
Strong programming skills in Python.
Ability to develop high-quality, secure, scalable enterprise-grade backend components and follow compliance.
Work from the office full-time (remote not available).
Desired: 10+ years in Software Engineering and 3+ years in AI/ML space.

Fortinet Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fortinet and has not been reviewed or approved by Fortinet.

Affordable Benefits — Medical coverage includes a no-premium HDHP option with HSA funding alongside PPO/HMO choices, reducing employee costs at enrollment. Eligibility starts on the date of hire and includes company-paid life and disability coverage.
Wellbeing & Lifestyle Benefits — Mental-health access through Modern Health and an EAP offers therapy, coaching, and counseling resources. Lifestyle extras such as legal assistance, commuter benefits, pet-insurance discounts, and subsidized meals and snacks enhance everyday support.
Strong & Reliable Incentives — Compensation packages include annual bonuses, sales commissions, and stock awards. Earnings potential can be strong in sales when quotas are realistic and attainment is high.