AI Architect

* The AI Architect will primarily be responsible to design and implement scalable AI-driven cybersecurity solutions, including chatbot-based virtual Chief Information Security Officer (vCISO) systems and AI-powered document comparison models. * The role requires expertise in integrating AI solutions with enterprise platforms, ensuring security compliance, and optimizing MLOps/LLMOps workflows.

Key Responsibilities:

AI Solution Design & Development

• Architect scalable AI/ML models for cybersecurity applications, including threat detection, anomaly analysis, and automated compliance audits.
• Design chatbot-based vCISO systems leveraging LLMs (e.g., ClaudeV2, GPT-4) to simulate CISO decision-making and provide real-time security guidance.
• Develop AI models for document comparison, ensuring accuracy in detecting discrepancies, data extraction, gap analysis and pattern recognition across unstructured datasets.

Integration & Scalability

• Build modular architectures compatible with cloud platforms (AWS, Azure) and DevOps pipelines (Kubernetes, Docker).
• Implement MLOps/LLMOps workflows for seamless model deployment, monitoring, and updates.
• Ensure interoperability with existing security tools (SIEM, SOAR) and data governance frameworks.

Security & Compliance

• Apply PCI DSS, GDPR, PDPL and NIST frameworks to AI solutions, prioritizing data encryption, access control, and system hardening.
• Conduct risk assessments and audits to mitigate vulnerabilities in AI architectures.

Collaboration & Leadership

• Mentor cross-functional teams (data scientists, DevOps engineers) on AI best practices.
• Hiring and assessing the skills of employees reporting to them.
• Translate business requirements into technical specifications for stakeholders.

Qualifications:

• Master's in data science, AI, or related field. PhD preferred.
• Around 6 years in AI/ML architecture.
• Proficiency in TensorFlow, PyTorch, and LLMs (GPT-4, ClaudeV2).
• Expertise in cloud platforms (AWS Bedrock, Azure AI), MLOps tools (Kubeflow, MLflow), and DevOps (Git, Kubernetes).
• Hands-on experience with document comparison AI models, NLP, and anomaly detection algorithms.
• Track record of deploying scalable AI solutions in regulated industries (finance, healthcare).
• Familiarity with Data Mesh/Lakehouse architectures, hybrid cloud environments and standalone on-premises solutions.
• Strong communication skills for translating technical concepts to non-technical audiences.