Job Overview
We are seeking a highly skilled
Senior AI Platform Engineer to join our growing team and contribute to building our internal and customer facing
cutting edge AI solutions. This role focuses on backend development for cloud-based applications and the integration of AI technologies such as
Cloud Native Cognitive Services,
Agentic AI,
LLMs and more. The ideal candidate will have deep expertise in cloud infrastructure, scalable backend systems, and AI integration strategies.
Job Description
- Design, develop, and maintain the core backend infrastructure for our cutting edge AI Solutions
- Build and optimize APIs, microservices, and scalable cloud-based architectures
- Integrate AI technologies such as LLMs, RAG (Retrieval-Augmented Generation), and fine-tuned modelsinto cloud-native applications
- Develop robust data pipelines to support AI model inference, data storage, and real-time processing
- Collaborate with data scientists, product managers, and UX designers to translate business requirements into technical solutions
- Ensure system performance, scalability, and security by implementing best practices
- Automate infrastructure management using tools like Terraform, Bicep, or other Infrastructure-as-Code (IaC) frameworks
- Drive technical innovation and best practices within the engineering team
- Conduct code reviews, mentor junior engineers, and ensure high code quality standards
- Monitor and troubleshoot platform performance issues, ensuring minimal downtime and optimal performance
Job Specifications
- 5+ years of experience in backend development for cloud applications
- Strong proficiency in Python, C#, FastAPI or Node.jswith experience building scalable APIs and microservices
- Expertise in cloud platforms like Microsoft Azure, AWS, or Google Cloudwith a focus on AI services
- Experience with Microsoft Cognitive Services, Azure OpenAI, or similar AI frameworks
- Deep understanding of AI concepts such as RAG, fine-tuning, and prompt engineering
- Hands-on experience with containerization technologies like Docker and Kubernetes
- Experience with database systems (SQL and NoSQL) and vector databases for AI solutions
- Proven expertise in CI/CD pipelines, automated testing, and deployment strategies
- Strong problem-solving skills with a proactive and solution-oriented mindset
- Experience integrating Speech-to-Text, Text-to-Speech, and conversational AI frameworks
- Background in designing real-time data processing systems
- Familiarity with performance monitoring tools and logging frameworks
