Aprio PH - AI Engineer

Job Responsibilities:

Solution Design & Architecture:
• Design and architect end-to-end AI/ML solutions, ensuring they align with business objectives and scalability requirements.
• Define overall architecture and data pipelines, selecting appropriate AI tools and frameworks for each project.
• Ensure best practices are applied in security, scalability, and maintainability of AI systems.
Development & Deployment:
• Build, test, and deploy AI and machine learning models on Azure platforms (Azure ML, Cognitive Services, Azure Data Factory, Azure Synapse), or other best of industry solutions.
• Develop APIs and integration points for seamless data exchange between AI solutions and existing business systems (e.g., Internal Systems/Databases, Microsoft Dynamics 365, SharePoint, Power BI).
• Implement CI/CD pipelines, containerization (Docker, Kubernetes), and automated testing to ensure efficient deployment and monitoring of AI models.
 Cloud Infrastructure & MLOps:
• Establish MLOps best practices for continuous integration, delivery, and monitoring of models.
• Optimize AI model performance for scalability and low latency in production.
• Implement solutions using infrastructure-as-code principles and tools to enhance reliability and scalability.
Collaboration & Consultation:
• Work closely with tax, audit, and advisory teams to identify use cases where AI can add value.
• Translate domain requirements into technical specifications and AI solutions.
• Provide technical guidance and mentorship to junior AI engineers and developers.
Research & Continuous Improvement:
• Stay current with advancements in AI.
• Experiment with and implement new AI techniques and tools to enhance service offerings.
• Develop Proof of Concepts (POCs) for innovative AI solutions.
Documentation & Support:
• Create and maintain comprehensive documentation for AI models, data pipelines, and system architecture.
• Ensure AI solutions comply with data privacy, security policies, and ethical AI guidelines.
• Provide training and support to other developers and end-users to increase AI literacy.

Qualifications:

• Proven experience in AI architecture, design, and deployment with Microsoft Azure Cloud Technologies, or similar industry best technologies (Azure ML, Cognitive Services, Azure Data Factory, Azure Kubernetes Service, etc.).
• Proficiency in programming languages such as C#, Python, R, or JavaScript.
• Strong understanding of machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, scikit-learn).
• Familiarity with Microsoft Power Platform (Power BI, Power Apps, Power Automate) and integrating AI models with these tools.
• Experience with DevOps tools and practices including CI/CD, containerization (Docker, Kubernetes), and automated testing.
• Knowledge of data architecture, databases, and data lakes (SQL, NoSQL, Azure Synapse, etc.).
• Knowledge and experience with vector databases or knowledge bases for retrieval-augmented generation.
• Knowledge and experience of prompt engineering and fine-tuning large models.
Soft Skills:
• Excellent analytical, problem-solving, and decision-making abilities.
• Strong communication skills, with the ability to translate complex technical concepts to non-technical stakeholders.
• Collaboration and teamwork skills with a proactive, innovative mindset.
Preferred Skills:
• Bachelor’s degree in Computer Science, MIS, or similar.
• Prior AI experience is a major plus.
• Experience with Automation tools such as UiPath or Blue Prism.
• Previous experience in the Accounting Technology Industry.
• Certifications in Microsoft Azure (e.g., Azure AI Engineer Associate).
• Experience with generative AI frameworks such as LangChain or Semantic Kernel