Senior AI Solutions - Lead

About the Job

Senior AI Solutions - Lead

Experience : 10 + years

Client Location : UAE

Notice Period : Only immediate joiners

Detailed Job Description

Key Responsibilities:

• Lead the architecture, design, and end-to-end delivery of complex AI/ML solutions.
• Define and implement AI strategy in alignment with enterprise goals and digital transformation initiatives.
• Translate business requirements into scalable and secure AI system architectures.
• Oversee the development and deployment of AI/ML models in production environments.
• Guide data scientists, engineers, and developers in adopting AI best practices and technologies.
• Drive MLOps and AI lifecycle automation including model training, versioning, testing, deployment, and monitoring.
• Design AI solutions integrated with enterprise platforms (Microsoft, Salesforce, ERP, CRM, data lakes, APIs).
• Ensure responsible AI practices, including ethical considerations, bias mitigation, and regulatory compliance.
• Collaborate with C-level stakeholders and business units to assess use cases, prioritize projects, and define success metrics.
• Mentor and lead technical teams; influence architectural decisions across business units.

Required Technical Skills:

AI/ML Expertise:

• Strong knowledge of machine learning, deep learning, NLP, computer vision, and generative AI.
• Hands-on experience with frameworks like TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenAI APIs.

Architecture & System Design:

• Proven experience in designing scalable and secure cloud-native AI solutions.
• Deep understanding of microservices, APIs, event-driven architectures, and real-time inference systems.
• MLOps & DevOps:
• Experience with tools like MLflow, Kubeflow, Airflow, SageMaker Pipelines, Vertex AI Pipelines.
• Knowledge of CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).

Data & Integration:

• Familiarity with data engineering tools (Spark, Kafka), data lakehouses (Delta Lake, Snowflake), and ETL pipelines.
• Ability to integrate AI with enterprise platforms and legacy systems via RESTful APIs or middleware.
• Leadership & Soft Skills:
• Strong leadership experience managing multidisciplinary AI/ML teams.
• Ability to drive architecture governance, code quality, and technical standards.
• Excellent communication and presentation skills to influence technical and non-technical stakeholders.
• Strategic thinker with a passion for AI innovation and enterprise transformation.

Preferred Experience:

• 10+ years of experience in software or data architecture roles, with 4–5 years focused on AI/ML.
• Track record of delivering AI projects at scale in one or more of the following domains: financial services, healthcare, government, telecom, or retail.
• Familiarity with regulatory frameworks for data and AI (e.g., GDPR, HIPAA, ISO 42001).
• Preferred Certifications:
• AWS Certified Machine Learning – Specialty
• Microsoft Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• TOGAF or other architecture frameworks (optional but valuable)
• Responsible AI or ethical AI certifications (optional)