Senior AI Engineer

About the Team

The AI Center of Excellence is a multidisciplinary group of Data Scientists and AI Engineers who partner with Detection and Response teams to turn cutting-edge research into real-world security products. We leverage LLMs, agentic workflows, and behavioral modeling to stay ahead of evolving threats and ensure our customers remain secure.

About the Role

As a Senior Software Engineer – Data Science, your primary responsibility will be to drive the end-to-end delivery of ML and LLM-based solutions on AWS.

Specifically, your focus will be to:

• Design and implement sophisticated ML pipelines for security use cases, including malware detection and user behavioral analytics.

• Architect and maintain RAG pipelines and agentic AI workflows using toolchains like LangChain and LangGraph to automate complex security tasks.

• Optimize and deploy models within the AWS ecosystem, utilizing SageMaker and Bedrock while ensuring robust monitoring, drift detection, and retraining workflows.

• Collaborate and mentor across the team to establish architectural standards, conduct code reviews, and support the technical growth of junior engineers.

The skills and qualities you’ll bring include:
Core Skills

• Technical Ownership: Ability to take a project from a conceptual prototype to a high-quality production system.

• Analytical Problem Solving: Expertise in applying scientific computing and statistical modeling to unlabeled, large-scale data.

• Continuous Learning: A proactive approach to mastering emerging technologies in LLMs, Generative AI, and agentic systems.

Functional Skills

• Python Proficiency: Advanced experience with numpy, pandas, and scientific computing libraries.

• Machine Learning Frameworks: Hands-on expertise with scikit-learn and Deep Learning frameworks (PyTorch or TensorFlow).

• Generative AI Toolchains: Proven experience with HuggingFace, Transformers, LangChain, and LangGraph.

• Cloud Infrastructure: Strong experience deploying and operating ML workloads on AWS (SageMaker, Bedrock, Lambda, EKS).

• Vector Databases & RAG: Practical experience designing and tuning Retrieval-Augmented Generation pipelines.

• MLOps & CI/CD: Proficiency in managing model registries, versioning, and automated deployment via GitHub Actions or Jenkins.

• Security Domain Knowledge: Familiarity with threat detection, malware behaviour, or cybersecurity analytics.

• Model Explainability: Ability to implement and interpret model transparency tools like SHAP or LIME.

• LLM Evaluation: Experience using evaluation frameworks such as Promptfoo or HELM to ensure model quality and safety.

We know that the best ideas and solutions come from multi-dimensional teams. That’s because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don’t be shy - apply today.

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