AI Factory Manager (AIML & MLOps Leadership)

KalSoft is currently looking for an experienced AI Factory Manager (AI/ML & MLOps Leadership) to join Our team. This role is ideal for senior professionals with strong expertise in Data Artificial Intelligence Advanced Analytics and AI industrialization (AI Factory / MLOps). The candidate will be responsible for leading AI/ML teams managing enterprise AI programs and ensuring successful delivery of AI use cases into production environments.

• Lead AI/ML teams and programs focused on AI Factory and MLOps delivery.
• Drive AI/ML industrialization and ensure scalable deployment of AI solutions.
• Oversee development and execution of Machine Learning Deep Learning NLP and Generative AI solutions.
• Collaborate with business and technical stakeholders to deliver AI-driven business value.
• Ensure end-to-end lifecycle management of AI models from development to production.
• Guide teams on data engineering and big data platforms for AI solutions.
• Implement and manage cloud-based AI services and infrastructure.
• Ensure adoption of MLOps frameworks for automation deployment and monitoring.
• Identify and deliver AI use cases successfully into production.
• Provide leadership in AI governance standards and best practices.
• Drive strategic planning problem-solving and continuous improvement in AI initiatives.

• Minimum 10 years in Data AI or Advanced Analytics.
• At least 5 years in leadership roles managing AI/ML teams or programs.
• Proven experience in AI/ML industrialization (AI Factory / MLOps).
• Experience in banking financial services or fintech is highly preferred.
• Strong knowledge of Machine Learning Deep Learning NLP and Generative AI.
• Strong understanding of data engineering and big data platforms.
• Strong knowledge of cloud AI services (Azure AWS or GCP).
• Hands-on experience with Python R SQL and NoSQL databases.
• Experience working with MLOps frameworks and AI deployment pipelines.
• Exposure to Large Language Models (LLMs) and Generative AI use cases is preferred.
• Strong leadership team-building and stakeholder management skills.
• Strong strategic thinking analytical and problem-solving abilities.
• Proven track record of successfully deploying AI use cases into production environments.

• Exposure to Large Language Models (LLMs) and Generative AI use cases.
• Certifications such as Azure AI Engineer AWS ML Specialty or equivalent.
• Strong experience in delivering multiple AI use cases successfully into production.
• Strong leadership and team-building capabilities.
• Strategic thinking and strong problem-solving skills.