Senior Data Scientist (ML/AI and GenAI) Sana Commerce

At Sana Commerce, we are looking for a Senior Data Scientist (ML/AI & GenAI) to shape and operationalize the next generation of AI capabilities within our platform. You will play a key role in designing, building, and scaling intelligent features such as Retrieval-Augmented Generation (RAG), semantic search, and document processing systems.

This is a hands-on role that blends machine learning expertise with strong software engineering practices. You will work closely with Data Scientists, ML Engineers, Engineering Managers, and Product teams to deliver production-grade AI solutions within our Azure ecosystem.

GenAI Development & Architecture

• Design and build end-to-end Generative AI applications, including RAG pipelines, LLM orchestration, and semantic search solutions
• Collaborate with Product Managers and Engineering Leads to identify high-impact AI opportunities and translate them into scalable architectures
• Apply best practices for distributed ML systems to ensure modularity, maintainability, and scalability
• Optimize AI systems for latency, cost-efficiency, and data privacy
• Establish and promote architectural standards for AI/ML services

MLOps & Production Excellence

• Own the full lifecycle of ML models, from experimentation to production deployment
• Productionize models as scalable microservices using FastAPI, Docker, and Kubernetes (AKS)
• Implement and promote MLOps best practices, including CI/CD, monitoring, and data validation
• Ensure systems are observable, reliable, and aligned with engineering and security standards
• Translate complex AI concepts into practical, implementable solutions for engineering teams

Collaboration & Engineering Culture

• Work closely with Engineering Managers, Data Scientists, and Product teams to deliver impactful AI-driven features
• Mentor and coach team members on software engineering best practices (OOP, testing, system design)
• Establish technical guardrails and reference architectures for AI development
• Foster a culture of experimentation, knowledge sharing, and evidence-based decision-making
• Contribute to improving documentation and AI/ML knowledge across the organization

Hands-On Development & Innovation

• Build proof-of-concepts and run technical experiments to validate new approaches
• Contribute to design reviews and key architectural decisions involving AI/ML
• Stay close to delivery teams to ensure solutions are practical and production-ready
• Support the development of AI-powered features such as search, recommendations, and document intelligence