[Remote] Principal Engineer, AI
Note: The job is a remote job and is open to candidates in USA. Anaplan is a company focused on optimizing business decision-making through AI-infused planning and analysis. They are seeking a Principal Engineer, AI to work across the full stack of AI applications, building production-ready features that empower users to leverage GenAI within their planning workflows.
Responsibilities
- 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
Skills
- 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
- 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)
Company Overview
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