We're seeking a Principal Engineer, AI who can work across the full stack of Anaplan AI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. We look forward to collaborating in person! This role features a hybrid work model, with two days a week spent onsite in our New York office. Your Impact • 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. • Integrate and optimize LLMs for specific business planning use cases, including prompt engineering and RAG implementation. • Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language • Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics • Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations • Optimize model inference pipelines for performance, cost, and scalability in production environments • Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behavior. • Collaborate with data scientists to productionise ML models and forecasting algorithms Your Qualifications • Extensive hands-on professional experience in the field of Artificial Intelligence, Machine Learning, or related engineering domains. • End-to-end exposure in model lifecycle development, including extensive experience in training and deploying ML models in production environments. • Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. • Experience in fine-tuning LLMs for domain-specific enterprise applications. • Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments. • Experience with agentic frameworks and autonomous agent architectures. • Proficiency in Python and modern software development practices (testing, code review, CI/CD). • Proven track record of delivering complex technical projects on time with high quality Desirable • Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field • Hands-on experience with cloud-native ML infrastructure platforms • Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models • Experience with model serving frameworks (vLLM, TensorRT, Ray) • Experience with A/B testing and experimentation frameworks for AI features • Contributions to open-source ML projects or research publications • Experience with model observability tools (LangSmith, W&B, MLflow) #LI-SP1 Base Salary Range: $210,000-$285,000 USD