Principal Engineer (A.I.)

Join Anaplan as a Principal Engineer, AI, where you'll work across the full stack of AI applications, from model integration to building user interfaces. You'll lead the architecture, design, and deployment of scalable Generative AI and Machine Learning systems, develop end-to-end GenAI features, and collaborate with data scientists to productionize ML models. This role requires deep ML knowledge, strong software engineering skills, and extensive experience in Artificial Intelligence and Machine Learning.

• Lead the architecture, design, and deployment of scalable Generative AI and Machine learning systems into production environments.
• Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments.
• Collaborate with data scientists to productionise ML models and forecasting algorithms, ensuring scalable, reliable, and monitorable model deployments.
• End-to-end exposure in model lifecycle development, including extensive experience training and deploying ML models in production environments
• Experience with agentic frameworks and autonomous agent architectures
• Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns
• Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains
• Proven track record of delivering complex technical projects on time with high quality
• Proficiency in Python and modern software development practices (testing, code review, CI/CD)
• Experience in fine-tuning LLMs for domain-specific enterprise applications
• Experience with model observability tools (LangSmith, W&B;, MLflow)
• Contributions to open-source ML projects or research publications
• Experience with model serving frameworks (vLLM, TensorRT, Ray)
• Experience with A/B testing and experimentation frameworks for AI features
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
• Hands-on experience with cloud-native ML infrastructure platforms
• Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field