Overview
Principal Engineer, AI to design, deploy, and improve production Generative AI and Machine Learning systems across the full stack of AI applications.
What you'll do
- Lead architecture, design, and deployment of scalable GenAI/ML systems for production environments.
- Develop end-to-end GenAI features including backend API services, model integration, monitoring, evaluations, and deployments.
- Integrate and optimize LLMs for business planning use cases using prompt engineering and RAG.
- Build conversational interfaces and agentic workflows for natural-language planning tasks.
- Implement evaluation frameworks to measure and improve GenAI quality (accuracy, latency, user satisfaction).
- Expose AI capabilities via APIs to the platform and third-party integrations and optimize inference pipelines for performance, cost, and scalability.
What you'll need
- Extensive hands-on experience in Artificial Intelligence, Machine Learning, or related engineering domains.
- End-to-end model lifecycle experience training and deploying ML models in production.
- Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns.
- Strong expertise in MLOps and LLMOps for scalable, reliable, monitorable deployments.
- Experience with agentic frameworks and autonomous agent architectures.
- Proficiency in Python and modern software development practices including testing, code review, and CI/CD.
- Strong track record delivering complex technical projects on time with high quality.
Read the full description and apply on the company’s own careers page.
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