Security Engineer

Role Overview

Join our dynamic AI team to design, develop, and deploy cutting-edge machine learning and AI solutions. You will work on scalable backend systems, real-time prediction models, and advanced automation flows, driving measurable business impact across multiple domains. You will also ensure that AI models and workflows adhere to cybersecurity best practices.

• Lead the end-to-end design, development, and deployment of machine learning models and platforms, including LLMs, GANs, and recommendation engines.
• Design, develop, and fine‑tune AI/ML models for real‑time user behavior prediction, churn reduction, and customer experience automation.
• Apply RAG concepts, prompt engineering, anomaly detection, and changepoint detection to solve complex business problems.
• Develop and maintain scalable cloud‑native applications on AWS, Azure, or Google Cloud.
• Build robust and scalable APIs for integrating machine learning models and backend systems.
• Collaborate with cross‑functional teams for model experimentation and solution integration.
• Implement cybersecurity controls to safeguard AI workflows and ensure compliance.

• Formal training or certification and 3+ years of experience with AI models and workflows.
• Advanced proficiency in Python and relevant libraries (Pandas, Num Py).
• Hands‑on experience with frameworks and libraries including Tensor Flow, PyTorch, BERT/LLMs, Hugging Face, OpenCV, scikit‑learn, Flask, and React.
• Expertise in cloud and Dev Ops technologies, including AWS, Google Cloud, Azure, Docker, Kubernetes, Jenkins, and Git Lab.
• Skilled in working with databases such as MySQL, Mongo
  
  DB, Postgre
  
  SQL, and No
  
  SQL systems.
• Strong background in data science and AI, covering deep learning, NLP, GenAI, RAG concepts, prompt engineering, and data visualization.
• Experience in secure coding, model validation, and data privacy.
• Excellent problem‑solving, communication, and teamwork skills.

• Experience with LLM fine‑tuning, prompt engineering, and multi‑modal AI integration.
• Familiarity with CI/CD pipelines and automation tools.
• Knowledge of frontend frameworks (React, Next.js).
• Certifications in AI/ML, Kubernetes, AWS, or cybersecurity.
• Exposure to cybersecurity frameworks and compliance standards.