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 robust 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).

📌 AI Security / AI Engineer ( With Cyber Security Knowledege) (Mumbai)
🏢 KPMG Assurance and Consulting Services
📍 Mumbai