GenAI Architect

Shape the future of AI innovation with Cloudzone.

We’re looking for a GenAI Architect to lead the design and delivery of cutting-edge Generative AI solutions that empower our customers to innovate and scale. In this role, you’ll combine deep technical expertise, creative problem-solving, and strategic insight to architect AI systems end-to-end—from vision to implementation.

If you’re passionate about transforming ideas into intelligent systems and want to work hands-on with the newest AI technologies, this is your opportunity to make an impact.

What You’ll Do

• Design and architect end-to-end AI and Generative AI solutions tailored to customer business needs.
• Act as the technical lead on AI projects -mentoring teams and ensuring delivery excellence.
• Collaborate with clients to translate business challenges into scalable AI architectures.
• Utilize leading cloud-native services (e.g., Google Vertex AI, Azure OpenAI, AWS Bedrock) to design, deploy, and optimize AI systems.
• Establish and uphold best practices in responsible AI, governance, performance, and security.
• Contribute to pre-sales efforts, shaping technical proposals and solution strategies.

Requirements:

• 5+ years of experience in data engineering or related fields.
• 1+ years of hands-on work in AI/ML engineering or AI architecture.
• Deep practical knowledge of LLMs, vector databases, model tuning, and AI pipelines.
• Proven experience leading technical teams or serving as a solution architect.
• Expertise in at least one major cloud ecosystem (AWS, Azure..).
• Strategic mindset with strong analytical and problem-solving skills.
• Strong communication abilities - able to present and simplify complex AI concepts to diverse audiences.
• Experience in pre-sales or customer-facing roles is an advantage.
• Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or a related field.

Advantage:

• Multi-cloud or cross-platform AI experience (e.g., AWS Bedrock, SageMaker, Azure OpenAI).
• Understanding of MLOps / GenAIOps practices.
• Understanding of AI governance, compliance, and model lifecycle management.
• Experience in NLP, computer vision, or advanced analytics.