About the Role

We are looking for a Cloud-Native Engineer to design and build cloud and ai-native platforms and applications that run securely and reliably on AWS, Azure, or Google Cloud. Working within multi-disciplinary and global teams, you will help clients migrate, modernize, and “AI-enable” workloads—turning business requirements into cloud-native architectures that meet rigorous performance, security, and cost-efficiency targets.

Key Responsibilities

• Translate user stories and reference architectures into microservices, event-driven, and serverless designs.
• Build and maintain pipelines in Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
• Stand up data pipelines, feature stores, and ML inference endpoints (SageMaker, Vertex AI, Azure ML).
• Operationalize GenAI workloads—vector stores, prompt-engineering patterns, etc.
• Conduct architecture reviews, demos, and knowledge-transfer workshops.
• Produce well-structured design docs, runbooks, and hand-over guides.

Qualifications

• 3–5 years of professional software or platform engineering experience – any cloud
• Proven delivery of cloud-native solutions on at least one hyperscaler (AWS, Azure, GCP) using containers, serverless, or microservices.
• Hands-on proficiency with Terraform (or CloudFormation/Bicep/Pulumi) and at least one modern language (Go, Python, TypeScript/Node .js, Java)
• Familiarity with AI/ML workflows or willingness to learn rapidly.
• Comfort operating in Agile/Scrum teams and using JIRA, Git, and collaboration tools.
• Strong verbal and written communication skills to be able to explain complex cloud patterns to technical and non-technical stakeholders.
• Bachelor’s degree in computer science, Software Engineering, or equivalent
• Entrepreneurial drive and mindset operating in a fast-paced, high-growth environment