Senior AI Engineering Specialist

Job Title:

Senior AI Engineering Specialist

At our organization, we are looking for a highly skilled Senior AI Engineer to join our team. As an AI engineering specialist, you will be responsible for building and implementing large language models (LLMs) and machine learning algorithms to improve cybersecurity investigations, prioritization, and response.

The ideal candidate will have deep expertise in LLMs, workflow automation, and classical ML models. You will work at the intersection of LLM-driven automation, workflow orchestration, and classical ML models to improve how alerts are prioritized, classified, and contextualized.

In this role, you will directly reduce analyst fatigue and enable faster, more effective decision-making. Your work will directly influence the development of agentic AI systems, workflow automation, and recommendation engines within our cloud security platform.

We are looking for someone with strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection. Proficiency with LLM frameworks and APIs is also required. The ideal candidate should have hands-on experience building workflow automation with LLMs and integrating them into applications.

You will work closely with data scientists, ML engineers, security researchers, and software teams to build end-to-end solutions. Documenting models, workflows, and pipelines for reproducibility and knowledge sharing is essential.

• LLM Integration & Workflows: Build, fine-tune, and integrate large language models into existing systems. Develop agentic workflows for investigation, classification, and automated response. Apply techniques like Retrieval-Augmented Generation (RAG), prompt engineering, and fine-tuning.
• Machine Learning Development: Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification. You'll apply both classical models (AR, ARIMA, SARIMA) and modern architectures (XGBoost, LSTM, DeepAR, Temporal Fusion Transformer).
• Data Preparation & Feature Engineering: Collect, preprocess, and transform structured and unstructured data, including logs, text, and access patterns. Engineer features to maximize model interpretability and performance.
• Model Training & Deployment: Train and evaluate models using rigorous metrics (precision, recall, AUC, F1, etc.). Optimize hyperparameters and deploy ML and LLM models at scale into production with strong monitoring, drift detection, and observability.
• Collaboration: 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.

• A 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).
• Knowledge of NLP tasks such as text classification, summarization, and semantic search.
• 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.

Contact us to explore this opportunity further.