Senior Cloud AI Engineer
Job Description
Location: Lewisville, TX
Position Type: Full-Time
Hours: 9:00am to 5:00pm Weekdays (Monday – Friday)
Senior Cloud AI Engineer you will design, develop, and optimize AI-driven solutions in cloud environments, leveraging advanced machine learning models and scalable architecture. Will work extensively with large datasets, ensuring efficient data ingestion, processing, and management in cloud-based AI systems. Role will involve building robust data pipelines, implementing data governance strategies, and optimizing storage solutions to support AI applications. Collaborate with data scientists to refine AI models, ensuring they are trained and deployed using high-quality, well-structured data. Strong expertise in cloud computing, AI frameworks, database technologies, and data security practices will be essential for success in this role.
Minimum Degree Requirement: Bachelor’s degree or equivalent in Computer Science, Information Technology or Engineering or closely related field.
Minimum Work Experience:
2 years of experience
Key Responsibilities
AI Model Development and Deployment
- Design, train, and fine-tune machine learning models for cloud environments.
- Optimize algorithms for scalability, efficiency, and performance in real-time applications.
- Deploy AI models using cloud-native technologies like Kubernetes, TensorFlow Serving, or ML pipelines.
Data Engineering and Management
- Develop robust data pipelines for seamless AI model training and inference.
- Handle large datasets, ensuring efficient data ingestion, transformation, and storage in cloud platforms.
- Apply data governance strategies to maintain data integrity, security, and compliance with regulations like GDPR and CCPA.
Cloud Architecture and Optimization
- Design scalable AI infrastructure using cloud services such as AWS, Azure, or Google Cloud.
- Optimize cloud storage solutions, compute resources, and networking configurations for AI workloads.
- Implement best practices for cost-effective cloud AI operations, reducing overhead expenses.
Automation & Security
- Automate AI model training, deployment, and monitoring processes to improve efficiency.
- Integrate security protocols, encrypt sensitive data, and mitigate risks associated with AI-driven applications.
- Ensure compliance with industry standards for cybersecurity and ethical AI usage.
Collaboration and Innovation
- Work closely with data scientists, software engineers, and stakeholders to refine AI solutions.
- Participate in research and development to explore emerging AI trends and technologies.
- Contribute to the continuous improvement of AI architectures and methodologies within the organization.
Performance Monitoring and Troubleshooting
- Implement AI performance tracking mechanisms to assess model accuracy and efficiency.
- Identify and resolve system bottlenecks, ensuring AI applications meet business objectives.
- Conduct regular audits and updates to enhance AI-driven functionalities.
Technical Experience
- 2 years of experiencein platforms such as AWS, Azure, or Google Cloud, with handson experience deploying AI models.
- 1 year of experience in TensorFlow, PyTorch, Scikit-learn, or other AI/ML tools for model development and optimization.
- 2 years of experience with Databricks for large-scale data processing, Spark for distributed computing, and efficient ETL workflows.
- 2 years of experience in Power BI and Tableau for visualizing AI-driven insights, creating interactive dashboards, and communicating data findings effectively.
- 2 years of experience with databases (SQL, NoSQL), data lakes, and processing frameworks to support scalable AI solutions.
- 1 year of experience with strong coding skills like Python, Java, or .NET • 1 year of experience with Kubernetes, Docker, and serverless computing for scalable AI deployment.
- 1 year of experience to build, deploy, and integrate AI models via RESTful APIs and microservices architecture.
- 1 year of experience on CI/CD pipelines, automated AI deployment, and monitoring tools for model performance.
- 1 year of experience with Git, GitHub, or Bitbucket for efficient code management and teamwork. 1 year of knowledge with automation techniques for BI processes.
