AI Engineer

Responsibilities

• Research, prototype, and productionize machine learning models for ITSM use cases (ticket triage, incident prediction, workflow recommendations, CMDB inference).
• Build scalable training and inference pipelines that integrate seamlessly into the core platform.
• Experiment with LLMs, embeddings, and retrieval-augmented generation (RAG) for IT knowledge and workflow automation.
• Partner with engineers and product managers to define AI-first features that differentiate our platform.
• Evaluate performance, optimize models, and ensure reliability, scalability, and cost-efficiency of AI systems.
• Stay current with advances in machine learning, LLMs, and AI infrastructure, and apply them pragmatically.

Qualifications

• Bachelor’s or Master’s in Computer Science, AI/ML, or related field; PhD is a plus.
• Strong software engineering fundamentals (Python preferred) and experience with ML frameworks such as PyTorch or TensorFlow.
• Experience with one or more of: natural language processing (NLP), large language models (LLMs), information retrieval, graph ML, or time-series forecasting.
• Understanding of modern MLOps practices: model versioning, deployment, monitoring, and lifecycle management.
• Comfort working in a fast-paced startup environment with end-to-end ownership.
• Bonus: experience applying AI in enterprise software or ITSM contexts.