Senior AI/ML Specialist YAZWAA RECRUITMENT - SOLE PROPRIETORSHIP L.L.C.

Operational Responsibilities:

AI/ML Solution & Use Case Development

• Own the full lifecycle of AI use cases from concept to production: ideation, feasibility analysis, prototyping, design, development, deployment, and scaling.
• Collaborate with stakeholders to identify high-value business challenges and translate them into AI/ML use cases.
• Build advanced ML/DL and agentic AI solutions, including RAG pipelines and autonomous agents.
• Develop reusable AI components, frameworks, and best practices for enterprise adoption.

Data Engineering & Management

• Design and manage data pipelines for ingestion, transformation, and governance of structured/unstructured data.
• Work with data lakes, warehouses, and vector databases to enable semantic search and retrieval.
• Ensure data quality, lineage, and compliance for AI workloads.

MLOps & Deployment

• Implement MLOps pipelines (CI/CD for ML, monitoring, retraining, and drift detection).
• Deploy models on cloud-native platforms (AWS, Azure, GCP) with focus on scalability, cost, and performance.
• Monitor production AI systems, ensuring availability, explainability, and fairness.

Collaboration & Stakeholder Engagement

• Partner with business, product, and engineering teams to ensure AI use cases align with organizational goals.
• Provide technical leadership and mentorship to junior engineers and data scientists.
• Produce high-quality documentation including BRDs for AI use cases, technical specifications, and solution blueprints.

Ethical & Responsible AI

• Ensure responsible AI practices across the full AI lifecycle (bias detection, transparency, compliance).
• Champion AI governance and model interpretability in production environments.

Technical Skills:

• Experience building end-to-end AI use cases: ideation, prototyping, deployment, monitoring, and iteration.
• Knowledge of agentic AI frameworks (LangChain, LlamaIndex, AutoGPT-like agents).
• Proficiency with RAG pipelines using vector databases (FAISS, Milvus, Pinecone, Weaviate).
• Strong background in data management, data engineering and governance (Spark, Airflow, Pandas, dbt).
• Experience with MLOps pipelines, CI/CD, monitoring, and model lifecycle management.
• Familiarity with API management and enterprise system integration for embedding AI services.
• Knowledge of UI/UX principles for building AI-enabled dashboards and user experiences.
• Awareness of AI ethics, bias mitigation, and responsible AI practices.