AI Operations Analyst / AI Operations Specialist / AI Solutions Analyst

Role Description

Support the deployment, monitoring, and optimization of Artificial Intelligence (AI) solutions to ensure reliable, scalable, and efficient business operations. This role is responsible for coordinating AI implementation projects, monitoring AI model performance, analyzing operational data, troubleshooting AI-related issues, and supporting the integration of AI technologies into business processes. The successful candidate will work closely with data scientists, machine learning engineers, software developers, product managers, and business stakeholders to ensure AI systems operate effectively and deliver measurable business value. The role also involves evaluating AI performance metrics, supporting MLOps processes, maintaining AI documentation, monitoring data quality, ensuring compliance with AI governance standards, and identifying opportunities to improve AI-driven workflows, automation, and operational efficiency.

Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Software Engineering, Business Analytics, or a related field.
• Proven experience in AI operations, machine learning operations (MLOps), business analytics, AI implementation, digital transformation, or technology consulting roles.
• Strong understanding of Artificial Intelligence (AI), Machine Learning (ML), Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), intelligent automation, and AI-powered business applications.
• Experience supporting AI solution deployment, model monitoring, performance evaluation, incident management, and operational support.
• Proficiency in SQL and programming languages such as Python, with experience using REST APIs and integrating AI services into enterprise applications.
• Familiarity with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), including AI and machine learning services.
• Experience with MLOps tools and technologies such as MLflow, Kubeflow, Databricks, Docker, Kubernetes, CI/CD pipelines, and model versioning is highly desirable.
• Knowledge of AI frameworks and platforms such as TensorFlow, PyTorch, LangChain, Hugging Face, OpenAI APIs, or similar AI ecosystems.
• Strong analytical, troubleshooting, and problem-solving skills with the ability to diagnose AI system issues, optimize operational performance, and recommend data-driven improvements.
• Excellent communication and stakeholder management skills with the ability to collaborate effectively across technical, operational, and business teams.
• Familiarity with AI governance, responsible AI principles, data privacy regulations, cybersecurity, and enterprise risk management is an advantage.
• Professional certifications in AI, cloud computing, data engineering, Agile, or project management are considered an advantage.
• A proactive, innovative, and results-oriented professional with a passion for operational excellence, emerging AI technologies, and delivering secure, scalable, and high-performing AI solutions that drive business transformation and continuous improvement.