Lead Cyber Security AI Engineer

As a member of Honeywell's Buildings Automation (BA) team with the AI Cyber Center of Excellence, you will play a crucial role in driving cybersecurity architecture in AI/ML/GEN-AI. Your primary focus will be on engineering solutions for endpoint, mobile, cloud, and standalone products. You are expected to be a risk and cybersecurity professional with extensive practical experience in testing, designing architecture, and driving product innovations with AI/ML/GEN-AI. Key Responsibilities: - Drive Honeywell COE Gen AI strategy, considering security, safety, and integrity of services for current and future state landscape & roadmap. - Provide Subject Matter Expertise on Generative AI adoption and impactful deployment for cybersecurity across internal architecture, third party integration, and custom models. - Collaborate with IT, Technical teams, Business SMEs to define architectural cyber frameworks, common standards, and solutions for product engineering. - Work closely with researchers, developers, and data scientists to implement and optimize AI/ML models in production environments. - Perform Market Research to identify new opportunities, ideas, and technology trends for adoption, collaborating with Vendors and Industry leaders. - Engage with Chiefs, Fellows, other Tech talents, and Tech forums to align Cyber across SBGs of engineering and IT, leveraging best practices/ideas. - Utilize existing BA and Honeywell ecosystem to collaborate with Universities and Startups to accelerate New Idea evaluation and incubation. - Coach & develop the next set of Cyber Researchers, Data Scientists, Leads, Pen-Testers, and Engineering teams. Qualifications Required: - Overall 10+ years of experience, with at least 5 years in cybersecurity focusing on identifying security risks, best practices, and developing solutions. - Ability to articulate, document, and produce guides, instructions, and present cybersecurity AI methods and techniques. - Possess risk management and cybersecurity certifications or relevant experience. AI/ML Skills: - Proficiency in Python, R, SQL, and common AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn). - Solid understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, etc. - Working knowledge of LLM models like Gemini, Llama, GPT, DALL-E, and frameworks like LangChain & Vector databases like Faiss, Pinecone. - Experience in fine-tuning LLM using LoRA/QLoRA techniques. - Ability to develop APIs and microservices to support Gen AI/ML applications.,