AI Engineering / Architect
Job description
Key Responsibilities:
- Design and Development:
- Design scalable cloud-based Generative AI solutions that integrate state-of-the-art generative AI models.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Develop and maintain architectural blueprints and technical documentation.
- Cloud Infrastructure:
- Architect secure and scalable cloud infrastructures that support the deployment and operation of generative AI models.
- Ensure high availability, data integrity, and compliance with industry standards and best practices.
- Optimize cloud resources for performance, cost-efficiency, and scalability.
- Security and Compliance:
- Implement robust security measures to protect data and AI models from unauthorized access and cyber threats.
- Ensure compliance with relevant industry standards, regulations, and data privacy laws.
- Conduct regular security assessments and audits to identify and mitigate potential risks.
- Collaboration and Leadership:
- Work closely with data scientists, machine learning engineers, and other stakeholders to integrate AI models into production environments.
- Provide technical leadership and mentorship to junior team members.
- Stay up-to-date with the latest advancements in AI and cloud technologies and incorporate them into the architecture.
- Performance Monitoring and Optimization:
- Monitor the performance of deployed AI models and cloud infrastructure.
- Identify and resolve performance bottlenecks and scalability issues.
- Implement continuous improvement processes to enhance system performance and reliability.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience as an AI Architect, Cloud Architect, or similar role.
- Strong expertise in designing and deploying cloud-based AI solutions using platforms such as AWS, Azure, or Google Cloud.
- In-depth knowledge of generative AI models, machine learning frameworks, and AI deployment best practices.
- Experience with cloud infrastructure, including networking, storage, and security.
- Familiarity with industry standards and regulations related to data privacy and security.
- Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
- Strong communication and collaboration skills.
Preferred Skills:
- Familiarity with big data technologies (e.g., Hadoop, Spark).
- Experience in natural language processing (NLP).
- Familiarity with big data technologies and data engineering.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
- Certification in cloud architecture or AI/ML is a plus.