Advanced AI Security Specialist

1 day ago

Kota, Rajasthan, India beBeeCybersecurity Full time ₹ 40,00,000 - ₹ 50,00,000
Expert in AI Cybersecurity

We are seeking a highly skilled Senior AI Engineer to join our team. With expertise in large language models (LLMs) and machine learning, you will craft intelligent systems that streamline cybersecurity investigations and enhance response capabilities.

This is an opportunity to leverage your technical acumen and hands-on experience to develop cutting-edge solutions. You will work at the intersection of LLM-driven automation, workflow orchestration, and classical ML models to optimize alert prioritization, classification, and contextualization.

Your contributions will directly impact the development of agentic AI systems, workflow automation, and recommendation engines within our cloud security platform.

Key Responsibilities:
  • Integrate LLMs into existing systems, develop workflows for investigation, classification, and automated response using techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning.
  • Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification using classical and modern architectures.
  • Collect, preprocess, and transform data, engineer features for model interpretability and performance, and apply knowledge of NLP tasks such as text classification, summarization, and semantic search.
  • Train and evaluate models using rigorous metrics, optimize hyperparameters, and deploy ML and LLM models at scale into production with strong monitoring, drift detection, and observability.
  • Work closely with data scientists, ML engineers, security researchers, and software teams to build end-to-end solutions, document models, workflows, and pipelines for reproducibility and knowledge sharing.
Requirements:
  • Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
  • 5+ years of experience in ML/AI with at least 3 years deploying production-grade systems.
  • Strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection.
  • Proficiency with LLM frameworks and APIs (OpenAI, Hugging Face, LangChain, LlamaIndex).
  • Hands-on experience building workflow automation with LLMs and integrating them into applications.
  • Solid programming skills in Python (PyTorch, TensorFlow, scikit-learn).
  • Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and MLOps best practices.
  • Strong problem-solving, analytical, and communication skills.
  • The ability to thrive in a fast-paced, evolving environment.

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