Principal Engineer, AI

• 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

• 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)

• Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.

• Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.

All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan , please send an email to before taking any further action in relation to the correspondence.

Candidate data processed during our recruitment activities is handled in accordance with our Candidate Privacy Notice. This may include the use of artificial intelligence or automated tools to assist our team in evaluating qualifications.

Originally posted on Himalayas