AI Security / AI Engineer ( With Cyber Security Knowledege)

Role & responsibilities

We are seeking a skilled and innovative AI Security Engineer / AI Engineer with 2 to 7 years of experience to design, develop, secure, and deploy AI/ML solutions. The ideal candidate should possess strong expertise in machine learning, generative AI, and cloud technologies, along with a good understanding of cybersecurity principles. This role will focus on building secure AI applications, implementing AI governance frameworks, mitigating AI-specific security risks, and enabling responsible AI adoption across the organization.

AI Engineering

• Design, develop, and deploy Machine Learning (ML), Deep Learning, and Generative AI solutions.
• Build and optimize AI/ML models using Python and popular frameworks.
• Develop and integrate GenAI applications utilizing Large Language Models (LLMs).
• Implement prompt engineering, Retrieval-Augmented Generation (RAG), and AI agent frameworks.
• Fine-tune and optimize AI models for performance, scalability, and business requirements.
• Collaborate with data engineers and business stakeholders to deliver AI-driven solutions.

AI Security & Governance

• Assess and mitigate AI-related security risks including model poisoning, prompt injection, adversarial attacks, and data leakage.
• Implement AI security controls, monitoring, and governance frameworks.
• Conduct security reviews of AI applications and machine learning models.
• Ensure compliance with Responsible AI, privacy, and regulatory requirements.
• Develop secure AI development lifecycle (AI-SDLC) practices.
• Establish AI model monitoring, drift detection, and risk management processes.

Cloud & MLOps

• Deploy AI solutions on cloud platforms such as Azure, AWS, or GCP.
• Build and maintain MLOps pipelines for model development, testing, deployment, and monitoring.
• Automate AI workflows using CI/CD practices.
• Manage model versioning, observability, and lifecycle management.

Preferred candidate profile :

• 2+ years of hands-on experience in AI/ML engineering.
• Strong programming skills in Python.

• Experience with AI/ML frameworks:

• TensorFlow
• PyTorch
• Scikit-learn

• LangChain / LlamaIndex

• Knowledge of:

• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• RAG Architectures

• AI Agents

• Experience with REST APIs and application integration.
• Familiarity with vector databases such as Pinecone, Chroma, FAISS, or Azure AI Search.
• Experience with Docker, Kubernetes, and DevOps practices.
• Knowledge of cloud platforms (Azure preferred, AWS/GCP acceptable).