Senior / Principal AI Engineer

We are seeking a highly skilled and motivated AI Engineer with expertise in large language models (LLMs), AI workflows, and machine learning. This role combines deep technical knowledge in ML/AI with hands-on experience building intelligent, production-ready systems that enhance cybersecurity investigation, prioritization, and response. 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—reducing fatigue and enabling faster, more effective decision-making.

Your work will directly influence the development of agentic AI systems, workflow automation, and recommendation engines within AiStrike’s cloud security platform. Key Responsibilities

LLM Integration & Workflows:

Build, fine-tune, and integrate large language models (LLMs) into existing systems. Develop agentic workflows for investigation, classification, and automated response in cyber security. Apply techniques like retrieval-augmented generation (RAG), prompt engineering, and fine-tuning for domain-specific tasks.

Machine Learning Development:

Design, implement, and optimize ML models for prioritization, ranking, clustering, anomaly detection, and classification. Apply both classical forecasting models (AR, ARIMA, SARIMA, ES) and modern architectures (XGBoost, LSTM, DeepAR, N-BEATS, 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, Evaluation, and Deployment:

Train and evaluate models using rigorous metrics (precision, recall, AUC, F1, etc.).Optimize hyperparameters and fine-tune LLMs for task-specific improvements. Deploy ML/LLM models into production at scale with strong monitoring, drift detection, and observability.

Collaboration & Documentation:

Work closely with data scientists, MLengineers, security researchers, and software teams to build end-to-end solutions. Document models, workflows, and pipelines for clarity, reproducibility, and knowledge sharing. Requirements

Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
5+ years of experience in ML/AI, including 3+ years deploying production-grade systems.
Experience contributing to publications (patents, libraries, or peer-reviewed papers) is a plus.
Strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection.
Proficiency with LLM frameworks and APIs (OpenAI, Hugging Face Transformers, LangChain, LlamaIndex).
Hands-on experience building workflow automation with LLMs and integrating them into applications.
Solid programming skills in Python (experience with PyTorch, TensorFlow, scikit-learn).
Knowledge of NLP tasks (text classification, summarization, embeddings, semantic search).
Experience with recommendation systems or reinforcement learning is a strong plus.
Proven track record of deploying ML/AI models into production environments with scalability in mind.
Familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes).
Understanding of MLOps best practices (CI/CD for ML, monitoring, retraining strategies).
Strong problem-solving and analytical mindset.
Excellent communication and teamwork skills.
Ability to work in a fast-paced, evolving startup environment.

Requirements

Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
5+ years of experience in ML/AI, including 3+ years deploying production-grade systems.
Experience contributing to publications (patents, libraries, or peer-reviewed papers) is a plus.
Strong knowledge of machine learning algorithms for classification, clustering, ranking, and anomaly detection.
Proficiency with LLM frameworks and APIs (OpenAI, Hugging Face Transformers, LangChain, LlamaIndex).
Hands-on experience building workflow automation with LLMs and integrating them into applications.
Solid programming skills in Python (experience with PyTorch, TensorFlow, scikit-learn).
Knowledge of NLP tasks (text classification, summarization, embeddings, semantic search).
Experience with recommendation systems or reinforcement learning is a strong plus.
Proven track record of deploying ML/AI models into production environments with scalability in mind.
Familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes).
Understanding of MLOps best practices (CI/CD for ML, monitoring, retraining strategies).
Strong problem-solving and analytical mindset.
Excellent communication and teamwork skills.
Ability to work in a fast-paced, evolving startup environment.

Why Join AiStrike

Shape the future of autonomous cyber defense.
Work directly with a founding team that helped scale Securonix to a $1B+ outcome.
Be part of a high-growth company at the forefront of AI and cybersecurity innovation.
Competitive compensation package including equity.

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