about 3 hours ago
Responsibilities
- Contribute to the architecture and take ownership of the design, development, and deployment of scalable Generative AI and Machine Learning systems.
- Develop end-to-end GenAI features including backend API services, model integration, monitoring, evaluations, and deployments.
- Integrate and optimize LLMs for specific business planning use cases, including prompt engineering.
- Build conversational interfaces and workflows that simplify complex planning tasks through natural language.
- Implement evaluation frameworks to measure and improve GenAI feature quality.
- 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.
- Implement monitoring, logging, and observability for GenAI systems.
- Participate in code reviews, lead technical design discussions, and mentor junior engineers.
Requirements
- Extensive hands-on experience in Artificial Intelligence, Machine Learning, or related engineering domains.
- End-to-end exposure in model lifecycle development with experience deploying and maintaining ML models in production.
- Strong knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Experience in fine-tuning LLMs for domain-specific enterprise applications.
- Experience with MLOps and LLMOps for scalable and reliable model deployments.
- Proficiency in Python and modern software development practices.
Tech Stack
MLflowPython