Work with a nationally ranked CPA and advisory firm that is passionate for what’s next. Aprio has 30 U.S. office locations, one in the Philippines and more than 2,100 team members that speak 60+ languages across the globe. By bringing together proven expertise, deep understanding, and strategic foresight for fast-growing industries, Aprio ensures clients are prepared for wherever life or business may take them. Discover a top-rated culture, vast growth opportunities and your next big career move with Aprio.
Join Aprio’s Information Technology team and you will help clients maximize their opportunities. Aprio is a progressive, fast-growing firm looking for a Lead AI Engineer to join their dynamic team.

TECHNICAL 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.

OTHER 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.

EDUCATION & EXPERIENCE:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years of experience in AI/ML development, architecture, and deployment.
• 3+ years of experience working with Microsoft Azure technologies preferred.
• Certifications in Microsoft Azure (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert, or Azure Data Scientist Associate) preferred.
• Experience with AI governance, ethics, and compliance in enterprise environments preferred.
• Experience with generative AI frameworks and tools such as LangChain, Semantic Kernel, or other LLM orchestration tools preferred.
• Experience in the accounting or financial services industry is a plus.
  The salary range for this opportunity is stated above. As such, an actual salary may fall closer to one or the other end of the range, and in certain circumstances, may wind up being outside of the listed salary range.
  The application window is anticipated to close on July 17th and may be extended as needed.

• 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.