Senior AI Engineer

The Senior AI Engineer will design, build, and scale Machine Learning and Generative AI solutions integrated into enterprise platforms, data infrastructure, and products. As part of the Cybersecurity team, this role will support the transformation of the Cyber Security Operations Center (CSOC) by developing AI-driven capabilities that enhance security operations, automation, and decision-making. Working closely with platform, backend, data, product, and cybersecurity teams, the Senior AI Engineer will own the end-to-end AI lifecycle, from experimentation and development to deployment and monitoring, while providing technical leadership and mentoring within the AI Engineering team.

Tasks and responsibilities

• Design, develop, and deploy Machine Learning and Generative AI solutions from experimentation through production.
• Build and review production-grade code and ensure seamless integration with existing platforms and services.
• Partner with platform, backend, data, product, and cybersecurity teams to define requirements and architecture decisions.
• Develop AI-driven capabilities that support the modernization and effectiveness of the Cyber Security Operations Center.
• Monitor model performance, reliability, and drift while troubleshooting production issues.
• Mentor junior engineers and provide technical guidance on complex challenges.
• Evaluate and adopt new tools, frameworks, and approaches to continuously improve existing systems.Contribute to AI governance, data privacy, compliance, and responsible AI practices.
• Document architecture decisions, system designs, and model behavior.
• Stay current with emerging AI and Machine Learning technologies and apply relevant innovations.

Requirements

• 5+ years of experience in AI/ML engineering with a proven track record of designing, building, and deploying Machine Learning and Generative AI solutions in production environments.
• Strong expertise in Python and hands-on experience with PyTorch or TensorFlow, together with solid knowledge of machine learning fundamentals, statistics, feature engineering, and model evaluation.
• Experience with LLM frameworks and techniques including LangChain, LlamaIndex, Retrieval-Augmented Generation (RAG), embeddings, agentic workflows, and modern AI application development.
• Proven ability to design scalable AI architectures, integrate AI capabilities into enterprise platforms, and develop API-driven services in cloud environments such as AWS, Azure, or GCP.
• Solid understanding of MLOps practices, including CI/CD, containerization, model deployment, monitoring, observability, and lifecycle management.
• Familiarity with vector databases, AI infrastructure tooling, and data governance, privacy, and compliance requirements such as GDPR.
• Experience mentoring engineers, collaborating with global cross-functional teams, and delivering solutions from proof of concept through production.
• Experience working with cybersecurity, security operations, threat detection, incident response, or related domains is highly desirable.
• Fluent English is required.