Senior AI Engineer

The client is looking for a Senior AI Engineer (5 Positions) to work in Dubai, UAE.

Role Overview:

The client is seeking highly skilled AI Agent Engineers to take a hands-on role in the development of the conversational and agentic systems that form the core of Project Aura. These engineers will be responsible for prompt engineering, building and fine-tuning agentic workflows, and integrating AI agents with diverse data sources and service APIs (e.g., EMRs, scheduling systems, lab results). The role demands both strong technical expertise and the ability to deliver scalable, production-grade solutions in a healthcare setting.

Key Responsibilities:

• Design, develop, and deploy AI-driven agents and conversational systems.
• Implement and optimize prompt engineering and fine-tuning workflows for LLMs.
• Build and maintain agentic workflows for healthcare use cases such as diagnostics, scheduling, and lab result interpretation.
• Integrate AI systems with third-party APIs and enterprise data sources (e.g., EMRs, lab systems).
• Develop and optimize RAG pipelines for efficient information retrieval and contextual reasoning.
• Work with Vector Databases and orchestration frameworks for multi-agent systems.
• Collaborate with cross-functional teams (product, clinical, and infrastructure) to deliver safe, scalable, and effective AI applications.
• Ensure system robustness, compliance, and data privacy in line with healthcare industry requirements.

Qualifications & Experience:

• Education: Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related fields.
• Experience: 5–8+ years of hands-on software/AI engineering experience, preferably in healthcare or regulated industries.
• Proficiency in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
• Demonstrable experience with:
  • Multi-agent system development.
  • Retrieval-Augmented Generation (RAG) pipelines.
  • Vector Databases (e.g., Pinecone, Weaviate, FAISS, Milvus).
  • API integration with external services and enterprise platforms.
• Experience building production-grade conversational AI systems.
• Knowledge of MLOps practices, containerization (Docker, Kubernetes), and cloud deployment (AWS, Azure, GCP).
• Familiarity with healthcare workflows, EMRs, and interoperability standards is a strong advantage.

Core Competencies:

• Strong problem-solving and system design skills.
• Ability to translate complex requirements into robust engineering solutions.
• Collaborative mindset, able to work with product managers, clinicians, and data scientists.
• Detail-oriented, with a focus on clinical safety, security, and compliance.
• Passion for advancing AI agent technologies in real-world applications.