Job Description

• 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.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate security analysis and vulnerability assessment documentation, validating outputs and ensuring sensitive data is handled appropriately.
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Applies approved tools to analyze and correlate incident data to identify, interpret, and summarize probability and impact of threats when determining specific vulnerabilities
• Leads delivery of continuity-related awareness, training and educational activities, and exercises
• Applies reuse-first, AI-assisted practices within SDLC/toolchain routines to strengthen security testing and control validation, ensuring traceability/auditability and alignment to resiliency and security expectations.
• 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.
• Implement cybersecurity controls to safeguard AI workflows and ensure compliance.

Required Skills

• Formal training or certification and 3+ years of experience with AI models and workflows
• Advanced proficiency in Python and relevant libraries (Pandas, NumPy).
• Hands-on experience with frameworks and libraries including TensorFlow, PyTorch, BERT/LLMs, Hugging Face, OpenCV, scikit-learn, SKLearn, Pandas, Flask and React.
• Expertise in cloud and DevOps technologies, including AWS, Google Cloud, Azure, Docker, Kubernetes, Jenkins, and GitLab.
• Skilled in working with databases such as MySQL, MongoDB, PostgreSQL, and NoSQL 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.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support security engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted code/security recommendations before use, escalating when uncertain and following security and data handling requirements.
• Excellent problem-solving, communication, and teamwork skills.

Preferred qualifications, capabilities, and 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.