
Cloud AI Engineer
2 days ago
About the Role:
We are seeking a skilled and experienced engineer to join our team at ibex. As a Senior Cloud & AI Engineer, you will play a pivotal role in designing and developing scalable, secure, and high-performance cloud-native solutions integrated with advanced AI capabilities.
You will be responsible for designing, developing, and maintaining scalable backend services and cloud infrastructure for our AI applications. You will also implement and integrate AI technologies such as LLMs, RAG, and fine-tuning using Microsoft Cognitive Services and other cloud-based AI solutions.
Key Responsibilities:
- Design and develop scalable backend services and cloud infrastructure for our AI applications
- Implement and integrate AI technologies such as LLMs, RAG, and fine-tuning using Microsoft Cognitive Services and other cloud-based AI solutions
- Develop APIs and microservices that deliver AI-driven functionality for our platform
- Collaborate with data scientists and AI engineers to integrate advanced AI models into cloud-based applications
- Evaluate system performance, scalability, and reliability by designing robust architecture patterns
- Build data pipelines and manage vector databases (e.g., Pinecone, Weaviate) to support AI model deployment
- Drive cloud infrastructure automation using tools like Terraform, Bicep, or ARM templates
- Establish CI/CD pipelines, monitoring systems, and automated testing frameworks to support engineering best practices
- Collaborate with product managers, UX designers, and other engineers to deliver impactful solutions that meet customer needs
Qualifications:
- 5+ years of experience in backend engineering for cloud platforms
- Proven experience in cloud platforms such as Microsoft Azure, AWS, or Google Cloud
- Strong programming skills in Python, C#, FastAPI or Node.js
- Experience in integrating cloud-native AI services such as Azure Cognitive Services, OpenAI, or equivalent platforms
- Deep understanding of RESTful APIs, microservices architecture, and serverless design patterns
- Strong knowledge of containerization technologies like Docker and orchestration tools like Kubernetes
- Familiarity with data pipelines, data lakes, and AI-driven data flow architectures
- Experience with cloud security best practices and designing secure APIs and services
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