AI Specialist

Description

This position is responsible for designing, developing, implementing, and maintaining artificial intelligence (AI) solutions that support and enhance the Ministry’s operational efficiency, decision‑making capabilities, and digital innovation initiatives. The AI Specialist will work across departments to identify opportunities for automation, data‑driven insights, and intelligent system integration while ensuring ethical, secure, and scalable AI practices. This role also requires a blend of technical expertise in AI/ML technologies, strong communication skills, and the ability to translate complex concepts into practical ministry applications.

• Design, develop, and deploy AI/ML models to support business and ministry objectives.
• Work with the IT Director to plan and design AI automations.
• Identify opportunities to implement AI‑driven automation across organizational processes.
• Build, train, test, and optimize machine learning and deep learning models.
• Collaborate with IT, data, and business teams to define AI requirements and use cases.
• Develop and maintain data pipelines for AI model training and inference.
• Design, develop, and deploy AI and machine learning solutions including natural language processing, computer vision, recommendation systems, and generative AI applications.
• Integrate AI capabilities into existing ministry systems such as content management, customer relationship management (CRM), broadcasting, and digital outreach platforms.
• Develop and maintain AI‑driven automation workflows to streamline repetitive tasks across departments, including data entry, scheduling, correspondence, and reporting.
• Build and manage prompt engineering strategies, fine‑tuning approaches, and retrieval‑augmented generation (RAG) pipelines for ministry‑specific use cases.
• Collaborate with content, media, and communications teams to leverage AI for content creation, transcription, translation, summarization, and personalization.
• Monitor AI model performance, accuracy, and ethical compliance; implement feedback loops and continuous improvement processes.
• Establish and enforce data governance, privacy, and security best practices as they relate to AI systems and the data they consume.
• Monitor model performance and implement improvements for accuracy, scalability, and efficiency.
• Ensure data quality, governance, and compliance with security standards.
• Research and recommend emerging AI technologies, tools, and frameworks.
• Develop natural language processing (NLP), computer vision, or predictive analytics solutions as needed.
• Create and maintain documentation for AI systems, models, and processes.
• Provide technical guidance and training to team members on AI‑related tools and practices.
• Assist in the evaluation and implementation of AI platforms such as Azure AI, AWS AI/ML, or other cloud‑based services.
• Ensure responsible AI usage, including bias mitigation, transparency, and ethical considerations.
• Participate in cross‑functional projects to enhance digital transformation initiatives.
• Support troubleshooting and resolution of AI‑related system issues.
• Stay current with advancements in AI, machine learning, and data science.
• May require participation in events or initiatives that involve AI‑enabled systems.
• Other duties as assigned by management.

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent work experience.
• 7+ years of hands‑on experience designing, building, and deploying AI/ML solutions in a professional environment.
• Demonstrated proficiency with AI/ML frameworks and libraries such as Tensor Flow, PyTorch, Hugging Face, Lang Chain, or similar.
• Experience with cloud‑based AI services including Azure AI, AWS Sage Maker, Google Vertex AI, or OpenAI API.
• Strong programming skills in Python; experience with JavaScript, SQL, and API development is a plus.
• Experience with large language models (LLMs), prompt engineering, fine‑tuning, and retrieval‑augmented generation (RAG).
• Familiarity with data engineering concepts including ETL pipelines, data warehousing, and database…