AI Application Support Specialist

The AI Application Support Specialist is responsible for supporting, maintaining, and optimizing AI-driven systems and applications across business functions. The role bridges technical AI development with operational application support, ensuring that AI solutions and social media automation tools run efficiently, ethically, and in alignment with organizational goals.

Key Responsibilities:

1. AI Systems and Application Support

• Provide end-user and technical support for AI platforms and enterprise AI applications.
• Monitor, troubleshoot, and resolve issues related to AI model performance, APIs, and system integrations.
• Support deployment, testing, and maintenance of machine learning models in production environments.
• Collaborate with AI developers, data scientists, and software engineers to enhance existing AI solutions.
• Manage AI application documentation, workflows, and knowledge repositories.
• Ensure uptime, reliability, and responsiveness of AI systems according to SLAs.

2. Optimization and Compliance

• Continuously evaluate AI models to ensure ethical use, accuracy, and compliance with privacy and data protection regulations (GDPR, etc.).
• Analyze system logs and user feedback to identify optimization opportunities.
• Implement continuous improvement processes for model retraining and version management.

3. AI-Driven Digital and Social Media Management

• Leverage AI tools to automate social media posting, analytics, and audience engagement.
• Develop and implement AI-assisted digital marketing strategies aligned with business objectives.
• Create, schedule, and monitor content across social media platforms (LinkedIn, Instagram, Facebook, X).
• Utilize generative AI for content creation and optimization.
• Track social media analytics and report actionable insights.

4. Training and Enablement

• Train internal teams on effective use of AI tools, automation, and best practices.
• Develop user manuals, quick-start guides, and conduct workshops.
• Support digital literacy initiatives and promote responsible AI adoption.

Key Result Areas (KRAs):

1. Sourcing and implementation: Source and implement AI-Driven Tools and Application for business functions

2. AI System Reliability: Optimum uptime and minimal system downtime.

3. Issue Resolution: Provide technical support and tickets shall be resolved within SLA.

4. AI Model Optimization: Regular updates and measurable improvement in model accuracy/performance.

5. Compliance & Ethics: Zero violations of data privacy or AI ethics guidelines.

6. Social Media Automation: Successful implementation of AI-driven content scheduling and analytics.

7. Training & Adoption: Training targeted employees to be trained and proficient in AI tools.

Key Performance Indicators (KPIs):

1. AI-Driven Applications and Tools Sourcing and implementation

a. Mapping and executing AI-Driven tools and application ≥ 4 per year

b. Tools and application sourced and implemented ≥ 4 per year

c. Upgradation of tools and applications ≥ 6 per year

2. System Support of AI application

a. Uptime ≥ 99%

b. Average resolution time per support ticket ≤ 24 hours

c. Number of recurring issues resolved permanently ≥ 90%

3. AI Model Management

a. Accuracy and performance score improvement +10% quarterly

b. Frequency of model retraining and documentation updates Quarterly

4. Compliance Number of data / privacies

a. Incidents to be Zero

b. Adherence to audit/compliance reports 100%

5. Social Media Management Engagement rate

a. Growth across platforms +15% quarterly

b. Response time to social media interactions < 2 hours (business hours)

c. Campaign ROI improvement via AI tools +10%

6. Training & Collaboration

a. Number of AI workshops conducted ≥ 6 per year

b. User satisfaction on AI tools (survey score) ≥ 85%

Qualifications and Experience:

• Bachelor’s degree in Computer Science, Data Science, Information Technology, Digital Marketing, or related field.
• 3–5 years of experience in AI application support, digital transformation, or AI-assisted social media management.
• Strong experience with generative AI tools, cloud AI services, and social media APIs.
• Certifications in AI/ML, Azure AI Engineer, or Digital Marketing (preferred).

Technical Competencies

• Strong understanding of AI/ML frameworks (TensorFlow, PyTorch, Azure AI, Open AI, Copilot).
• Proficiency in Python, SQL, and APIs for data integration and automation.
• Experience with social media management tools (Hootsuite, Sprout Social, Buffer).
• Familiarity with cloud platforms (AWS, Azure, Google Cloud) and data governance principles.
• Knowledge of SEO, digital marketing analytics, and AI-based campaign optimization.
• Experience in AI content generation tools (ChatGPT, DALL·E, Midjourney, Jasper).

Behavioral Competencies

• Analytical thinking and problem-solving.
• Attention to detail and proactive issue resolution.
• Excellent written and verbal communication.
• Collaboration and cross-functional teamwork.
• Ethical judgment in AI and data handling.
• Creativity and adaptability in using AI for digital transformation.

Job Types: Full-time, Permanent

Application Question(s):

• What is your salary expectations?
• What is your notice period to join?
• Are you willing to relocate to Ras Al Khaimah?

Education:

• Bachelor's (Preferred)

Experience:

• content generation tools (ChatGPT, DALL.E Jasper): 3 years (Required)
• AI application support, digital transformation: 5 years (Required)
• AI/ML frameworks TensorFlow, PyTorch, Azure AI, Copilot: 5 years (Required)

Language:

• English (Required)

License/Certification:

• AI/ML or Azure AI Engineer (Required)