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For Companies At a Glance
- Tasks: Design and implement cutting-edge cloud-based AI solutions while collaborating with diverse teams.
- Company: Join a leading global firm known for innovation and excellence in technology.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology, making a real impact in a dynamic environment.
- Qualifications: Bachelor's or Master's in Computer Science; experience in AI and cloud architecture required.
- Other info: Ideal for tech enthusiasts eager to learn and grow in a fast-paced setting.
The predicted salary is between 43200 - 72000 £ per year.
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. 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.
AI Engineering / Architect employer: Ernst & Young Advisory Services Sdn Bhd
Contact Detail:
Ernst & Young Advisory Services Sdn Bhd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineering / Architect
✨Tip Number 1
Familiarise yourself with the latest generative AI models and cloud platforms like AWS, Azure, or Google Cloud. This knowledge will not only help you understand the technical requirements but also demonstrate your commitment to staying current in the field.
✨Tip Number 2
Network with professionals in the AI and cloud engineering space. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn about the latest trends and challenges in AI architecture.
✨Tip Number 3
Showcase your problem-solving skills by discussing real-world scenarios where you've optimised cloud resources or improved system performance. Be prepared to share specific examples during interviews to highlight your hands-on experience.
✨Tip Number 4
Stay updated on industry standards and regulations related to data privacy and security. Being knowledgeable about compliance will set you apart as a candidate who understands the importance of secure AI solutions.
We think you need these skills to ace AI Engineering / Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI architecture and cloud solutions. Emphasise your expertise with platforms like AWS, Azure, or Google Cloud, and include specific projects that showcase your skills in generative AI.
Craft a Compelling Cover Letter: Write a cover letter that connects your background to the job description. Discuss your experience with cross-functional collaboration and how you've successfully integrated AI models into production environments.
Showcase Technical Skills: In your application, clearly outline your technical skills related to AI and cloud infrastructure. Mention any certifications you hold in cloud architecture or AI/ML, as well as your familiarity with big data technologies and machine learning frameworks.
Highlight Problem-Solving Abilities: Provide examples of how you've tackled performance bottlenecks or scalability issues in previous roles. This will demonstrate your problem-solving skills and ability to work in a fast-paced environment, which is crucial for this position.
How to prepare for a job interview at Ernst & Young Advisory Services Sdn Bhd
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with cloud platforms like AWS, Azure, or Google Cloud. Highlight specific projects where you've designed and deployed AI solutions, focusing on the technical challenges you faced and how you overcame them.
✨Demonstrate Collaboration Skills
Since the role involves working closely with cross-functional teams, be ready to share examples of how you've successfully collaborated with data scientists and machine learning engineers. Emphasise your ability to translate business requirements into technical solutions.
✨Discuss Security and Compliance Knowledge
Given the importance of security in this role, prepare to talk about your understanding of data privacy laws and industry standards. Share any experiences you have with implementing security measures and conducting audits to protect AI models.
✨Stay Updated on AI Trends
Make sure to mention your commitment to staying current with advancements in AI and cloud technologies. Discuss any recent developments you've incorporated into your work, demonstrating your proactive approach to continuous improvement.
