GenAI Engineer

Weare seeking a skilled and motivated GenAI Engineer with 3–5 years of experienceto support the development and deployment of AI-driven solutions within thesecurity services domain. This role focuses on enhancing operationalefficiency, incident analysis, reporting automation, and smart surveillancesolutions using Azure and OpenAI technologies. You will work closely withoperations, IT, and security teams to deliver scalable and practical AIapplications.

Responsibilities

• Design and implement generative AI solutions tailored to security operations and business processes.
• Develop AI-powered tools for incident reporting, risk analysis, and operational insights.
• Integrate large language models (LLMs), such as GPT, into internal systems and workflows.
• Build and deploy APIs and backend services using Python and/or Java.
• Work with Azure services, including Azure Machine Learning, Cognitive Services, and Azure Functions.
• Develop data pipelines for processing security logs, reports, and operational data.
• Optimize AI models for real-time performance and scalability in security environments.
• Collaborate with security operations teams to identify automation opportunities.
• Monitor, maintain, and improve AI systems used in production.
• Ensure data privacy, compliance, and security standards are maintained in all AI solutions.
• Stay updated on advancements in AI relevant to security and surveillance technologies.

Requirements

• Bachelor's or master's degree in computer science, Engineering, or a related field.
• 3–5 years of experience in AI/ML, software engineering, or data engineering.
• Experience working with Azure services such as Azure Machine Learning, Cognitive Services, and Azure Functions.
• Hands-on experience integrating OpenAI models (e.g., GPT-3/4) into applications.
• Strong programming skills in Python and/or Java.
• Understanding of machine learning concepts and AI model deployment.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with handling structured and unstructured data (e.g., logs, reports, CCTV metadata).
• Exposure to cloud platforms such as AWS or Google Cloud is an advantage.
• Knowledge of containerization tools like Docker and Kubernetes.
• Familiarity with CI/CD pipelines and DevOps practices.
• Understanding of data security, privacy, and compliance standards is preferred.
• Experience in security, surveillance, or facility management domains is a plus.