• Supports the development and deployment of Artificial Intelligence and Machine Learning solutions • Builds, tests, and deploys components of AI/ML models and applications • Implements components of MLOps workflows including data pipelines, packaging, versioning, monitoring, and model retraining • Collaborates with IT and data teams to ensure AI solutions follow security, integration, and performance requirements. • Breaks down requirements into well-defined technical tasks and contributes implementation-level input during design reviews.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a Senior AI Operations & Automation Manager, a hands-on role combining automation engineering, AI implementation, and operational strategy. We are looking for an "Architect of Efficiency"—someone who can not only build complex technical systems but also think strategically about business operations to drive massive leverage. In this role, you will act as the founder's right hand for AI-driven operational leverage. You will be responsible for owning and expanding automation workflows across multiple portfolio companies, moving beyond simple task automation to full-scale process redesign. - Part-time: 20 hours per week (can grow to full time) - Remote: Fully remote, CET working hours - Engagement Type: Independent Contractor - Monthly Rate: $800-1100 (based on a 20-hour workweek; flexible depending on experience) What You’ll Do - Design, build, and maintain high-level workflows using n8n, Make.com, and Zapier. - Optimize existing automations and scale them across various business units. - Proactively analyze business processes to identify inefficiencies. - Redesign manual, repetitive, or error-prone workflows to maximize ROI and operational impact. - Build and deploy specialized AI-powered agents for tasks such as automated email handling, complex document generation, financial calculations, and internal support systems. - Seamlessly connect AI solutions into our existing stack, including ClickUp, various CRMs, email systems, and custom internal dashboards. - Ensure all automations are robust, fully documented, and built to scale without constant manual intervention. - Act as a strategic consultant to the founder, prioritizing technical initiatives based on their business value rather than just technical novelty. Qualifications - 5+ years in automation, operations engineering, or AI-integrated systems. - Strong, hands-on experience with n8n or Make.com. - Comfortable with APIs, webhooks, and complex system integrations. - Proven experience building AI agents or RAG-based chatbots for real-world operational use cases. - Understanding of LLMs and how to apply them effectively. - Ability to translate abstract business problems into concrete technical solutions. - High familiarity with ClickUp or similar enterprise-grade project management tools. - Self-starter who takes full accountability for project outcomes from conception to deployment. Nice-to-Haves - Experience working across diverse industries (E-commerce, SaaS, Real Estate, Services). - Ability to communicate technical concepts clearly to non-technical stakeholders. - A mindset focused on efficiency and leverage—you build what matters, not just what is "cool." Recruitment Process - Initial Interview - Client Interview - Offer & Onboarding

• Build the intelligence layer of Bizee's platform • Own AI systems for personalized recommendations and intelligent automation • Lead a team of 3-6 AI/ML engineers while being hands-on • Report to the Head of Platform and partner closely with Data, Product, and Growth teams • Build systems for recommendations, intelligent automation, AI infrastructure, and LLM integration • Hire, develop, and retain AI/ML engineers

• Design, train, and evaluate ML models for text and voice analysis • Own feature engineering, labeling strategies, and evaluation metrics • Build and evolve ML pipelines that support experimentation and continuous improvement • Collaborate with data engineering teams on ETL, data quality, and data versioning • Influence modeling approaches and technical direction across the product