Benefits and conditions

• Fully remote job.
• All required equipment will be provided.
• Dynamic and interesting work with lots of growth opportunities.

Requirements

Software Engineering Experience

• Over 8 years of experience in software engineering, including at least 5 years specializing in .NET-based full-stack development, with a strong foundation and hands-on expertise in Artificial Intelligence (AI).

SaaS Platform Development

• Proven experience in building multi-tenant SaaS platforms or projects, emphasizing tenant-specific processing and data isolation.
• Proficiency in designing and managing tenant-specific APIs and integrating them into multi-tenant architectures.

AI/ML Expertise

• Extensive experience in AI/ML model design and deployment, focusing on Natural Language Processing (e.g., GPT, BERT), predictive analytics, or Retrieval-Augmented Generation (RAG)-based solutions.

Backend Development

• Strong expertise in .NET Core and C# for developing APIs, backend services, and serverless solutions.
• Demonstrated experience with Azure Functions, Durable Functions, and serverless architectures.

Cloud and Big Data

• Deep knowledge of Azure services, including Azure Cognitive Services, Azure OpenAI, Azure AI Search, Azure OpenAI Models, Azure API Management, Cosmos DB, and Blob Storage.

Programming and Tools

• Proficiency in programming languages such as Python (for AI workflows) and C# (for APIs and backend development).
• Practical experience with CI/CD pipelines, infrastructure automation tools (e.g., Terraform, Azure Bicep), and DevOps best practices.

Nice to have

• Familiarity with modern front-end frameworks for web apps (e.g., React, Angular) is a plus.

Soft Skills

• Strong communication skills and interpersonal skills.
• High-level english communication is needed (B2+/C1).

Responsibilities

Preferred Qualifications

• Design and integrate AI/ML models (shared and tenant-specific) into the SaaS platform, enabling features such as NLP, RAG (Retrieval-Augmented Generation), and predictive analytics.
• Architect and implement pipelines for AI model training, fine-tuning, and deployment using Azure services like Azure Cognitive Services, Azure Machine Learning, and related tools.
• Define and implement strategies for tenant-specific AI processing, ensuring data and model isolation while optimizing performance.

Full-Stack Development

• Lead the design and development of APIs, web applications, and backend services using .NET Core and C#.
• Implement and manage serverless architectures using Azure Functions and Durable Functions, ensuring high scalability and performance.
• Contribute to the development and maintenance of the tenant portal, admin dashboards, and API gateway for seamless multi-tenant management.
• SaaS Architecture Collaboration
• Collaborate with the Cloud Architect to ensure the AI and full-stack components align with the overall SaaS architecture.

Leadership and Strategy

• Provide technical leadership to the AI and full-stack engineering teams, mentoring developers and promoting best practices in software design and AI integration.
• Define coding standards and architectural guidelines to ensure maintainability and scalability of the platform.

Performance and Optimization

• Monitor and optimize the performance of AI models, APIs, and web applications to meet SLA requirements.
• Develop scalable, multi-region solutions that ensure compliance with tenant-specific data residency requirements.