Engineering Manager - AI Platforms

Role Overview: Sia Partners is seeking an Engineering Manager AI Platforms to play a crucial role in designing and delivering next-generation AI and Generative AI platforms within Sias AI Factory. As an Engineering Manager, you will bridge the gap between Data Science research and production-grade software engineering, ensuring the scalability, security, and seamless integration of data-driven AI services. Your leadership will drive innovation, experimentation, and professional development, keeping Sia at the forefront of the AI landscape. Key Responsibilities: - Team Leadership & Mentoring: Manage, coach, and grow a team of Software Engineers, ML & GenAI Engineers. Conduct performance reviews, define career paths, and foster an inclusive environment for innovation. - Platform Strategy: Own the roadmap for Sias AI Platforms, evolving them into enterprise-grade foundations that support various workflows and automated model fine-tuning. - Data Science Excellence: Oversee the development of scalable machine learning workflows with best practices in statistical rigor and model validation. - MLOps & GenAIOps Governance: Drive the adoption of robust MLOps pipelines to ensure reliability and observability of deployed Data Science models. - Cross-Functional Collaboration: Partner with Lead Data Scientists, Product Managers, and Cloud Architects to align technical execution with business objectives. - Technical Oversight: Provide architectural guidance for complex AI integrations involving vector databases and multi-cloud environments. - Security & Compliance: Ensure AI platforms adhere to global security standards and implement Responsible AI guardrails. - Stakeholder Communication: Act as a technical advocate, translating complex capabilities into clear insights for executive leadership. Qualifications: - Experience: 8+ years in data/software space, with 3+ years in people management or technical leadership. - Data Science Mastery: Deep understanding of the Data Science lifecycle and advanced modeling techniques. - AI/GenAI Depth: Hands-on experience with LLMs and complex RAG architectures. - Platform Expertise: Proven track record with Kubernetes, Docker, and cloud-native AI services. - Infrastructure: Understanding of vector databases and distributed system design. - Management Skills: Experience in Agile/Scrum methodologies and managing globally distributed teams. - AI-Native Engineering Leadership: Experience with AI workflow tools. - Education: Bachelors or Masters degree in related field. - Soft Skills: Exceptional emotional intelligence and conflict resolution skills. Note: The additional details of the company were not included in the job description. Role Overview: Sia Partners is seeking an Engineering Manager AI Platforms to play a crucial role in designing and delivering next-generation AI and Generative AI platforms within Sias AI Factory. As an Engineering Manager, you will bridge the gap between Data Science research and production-grade software engineering, ensuring the scalability, security, and seamless integration of data-driven AI services. Your leadership will drive innovation, experimentation, and professional development, keeping Sia at the forefront of the AI landscape. Key Responsibilities: - Team Leadership & Mentoring: Manage, coach, and grow a team of Software Engineers, ML & GenAI Engineers. Conduct performance reviews, define career paths, and foster an inclusive environment for innovation. - Platform Strategy: Own the roadmap for Sias AI Platforms, evolving them into enterprise-grade foundations that support various workflows and automated model fine-tuning. - Data Science Excellence: Oversee the development of scalable machine learning workflows with best practices in statistical rigor and model validation. - MLOps & GenAIOps Governance: Drive the adoption of robust MLOps pipelines to ensure reliability and observability of deployed Data Science models. - Cross-Functional Collaboration: Partner with Lead Data Scientists, Product Managers, and Cloud Architects to align technical execution with business objectives. - Technical Oversight: Provide architectural guidance for complex AI integrations involving vector databases and multi-cloud environments. - Security & Compliance: Ensure AI platforms adhere to global security standards and implement Responsible AI guardrails. - Stakeholder Communication: Act as a technical advocate, translating complex capabilities into clear insights for executive leadership. Qualifications: - Experience: 8+ years in data/software space, with 3+ years in people management or technical leadership. - Data Science Mastery: Deep understanding of the Data Science lifecycle and advanced modeling techniques. - AI/GenAI Depth: Hands-on experience with LLMs and complex RAG architectures. - Platform Expertise: Proven track record with