GenAI & ML Systems Architect

Anaplan; Greater London; On-site; GBP 110,000 - 180,000; Full time

Job summary

Anaplan in the United Kingdom is seeking a Principal Machine Learning Engineer to span the full stack of Anaplan AI applications, from model integration to user interfaces, building production-ready GenAI features for business planning workflows.

You will lead architecture and deployment of scalable AI systems, integrate LLMs for enterprise use cases, and collaborate with data scientists to productionise forecasting algorithms and APIs for platform integrations.

Qualifications

• Extensive AI/ML experience including production systems.
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
• Experience with end-to-end model lifecycle in production environments.
• Strong Python and modern software development practices (CI/CD).
• Proven track record delivering complex ML projects on time.

Responsibilities

• Lead architecture, design, and deployment of scalable Generative AI systems.
• Develop end-to-end GenAI features including backend APIs and model integration.
• Integrate and optimize LLMs for enterprise planning use cases.
• Build conversational interfaces and agentic workflows for natural language planning.
• Implement evaluation frameworks for GenAI quality, latency, and user satisfaction.
• Design APIs exposing AI capabilities to Anaplan's platform and third-party integrations.
• Optimize production inference pipelines for performance and cost.
• Collaborate with data scientists to productionise ML models and forecasting algorithms.

Education

Master's or Ph.D. in CS/AI

Tools

Pinecone

Weaviate

Qdrant

vLLM

TensorRT

Ray

MLflow

LangSmith

W&B

Job description

Anaplan in the United Kingdom is seeking a Principal Machine Learning Engineer to span the full stack of Anaplan AI applications, from model integration to user interfaces, building production-ready GenAI features for business planning workflows.

You will lead architecture and deployment of scalable AI systems, integrate LLMs for enterprise use cases, and collaborate with data scientists to productionise forecasting algorithms and APIs for platform integrations.