Senior Lead Engineer, AI Architecture

Job description:

As a Sr Lead Engineer, you will lead the design, development, and implementation of internally built AI solutions leveraging Azure-based technologies, with a focus on Azure Vision, Azure Language, and Azure OpenAI Service. You will collaborate with cross-functional teams to ensure technical requirements satisfy business goals, identify AI opportunities, and design and build scalable and innovative solutions that drive business value. This role requires expertise in Azure AI services, software architecture, and strong leadership skills to guide and inspire the team towards successful AI initiatives.

What you will do:

• Solution Architecture: Design end-to-end AI solutions leveraging Azure Vision, Azure Language, and Azure OpenAI Service, considering factors such as data ingestion, preprocessing, modeling, deployment, and monitoring.

• Technical Leadership: Provide guidance and leadership to AI development teams, driving best practices, architectural standards, and ensuring alignment with Azure AI capabilities and industry trends.

• Requirement Analysis: Collaborate with technical stakeholders to refine requirements, understand use cases, and define AI solution objectives, ensuring alignment with business goals and priorities.

• AI Implementation: Lead the implementation of AI solutions, including data integration, model development, integration with Azure services (e.g., Azure Cognitive Services, Azure Machine Learning), and deployment to cloud environments.

• Custom Model Development: Develop custom machine learning models and algorithms using Azure Machine Learning, Azure Databricks, or other Azure-based tools, tailored to specific business needs and use cases.

• Integration and Orchestration: Integrate AI solutions with existing systems, applications, and data pipelines, leveraging Azure services such as Azure Data Factory, Azure Functions, and Azure Logic Apps for orchestration and automation.

• Performance Optimization: Optimize AI models and algorithms for performance, scalability, and efficiency, utilizing techniques such as distributed computing, parallel processing, and model tuning on Azure infrastructure.

• Security and Compliance: Ensure the security and compliance of AI solutions, adhering to Azure security baselines , data privacy regulations, and industry standards (e.g., GDPR, HIPAA).

• Monitoring and Maintenance: Implement monitoring and logging mechanisms to track the performance, reliability, and usage of AI solutions, and proactively identify and address issues to ensure uptime and availability.

• Documentation and Training: Create technical documentation, architecture diagrams, and best practice guidelines for AI development on Azure, and provide training and support to internal teams on Azure AI technologies and tools.

What you need:

• Bachelor's or master's degree in computer science, artificial intelligence, data science, or related field.

• 6+ years of experience in software engineering, data engineering, or AI architecture roles, with a focus on building AI solutions on Azure.

• Expertise in Azure AI services, including Azure Cognitive Services (Vision, Language, Speech), Azure Machine Learning, and Azure OpenAI Service.

• Strong programming skills in languages such as Python, R, or C#, and proficiency in Azure cloud technologies (e.g., Azure Synapse Analytics, Azure Data Lake, Azure Kubernetes Service).

• Experience in designing and implementing machine learning models, natural language processing (NLP), computer vision applications, and other AI technologies.

• Familiarity with DevOps practices, CI/CD pipelines, and infrastructure as code (IaC) tools for automated deployment and management of Azure resources.

• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders.

• Azure certifications such as Microsoft Certified: Azure AI Engineer Associate or Microsoft Certified: Azure Solutions Architect Expert are a plus.

• Certifications in AI-related disciplines is preferred (e.g., AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate).