Description

You will architect and design scalable, secure, and highly available distributed systems for an AI-driven enterprise platform.

Responsibilities

• Define backend service architecture strategies, including API design (REST/gRPC), data contracts, versioning, and deployment standards.
• Architect LLM inference systems featuring request routing, batching, caching, and cost optimization.
• Design intelligent service patterns such as Retrieval Augmented Generation (RAG) and agent-based architectures.
• Ensure system resilience through consistency models, caching strategies, fault tolerance, and observability (logs, metrics, traces).
• Implement secure-by-default designs including threat modeling, identity management, and encryption.

Required Skills

• 14+ years of experience in backend architecture and distributed systems.
• Hands-on development experience in .NET or .NET Core (mandatory).
• Strong expertise in microservices, event-driven architectures, and cloud-native principles.
• Deep understanding of system design fundamentals, including resilience patterns and performance tuning.
• Experience integrating LLMs and Generative AI services into enterprise platforms.
• Proficiency with cloud platforms, specifically AWS (preferred) or Azure/GCP.
• Solid DevOps and Platform Engineering skills: CI/CD pipelines, Infrastructure as Code (Terraform/ARM/CDK), and automated testing.
• Experience with data and streaming technologies: SQL/NoSQL databases, Kafka, and Redis.
• Strong operational focus with an SRE mindset, including incident response and reliability engineering.

Preferred Skills

• Working experience with additional ecosystems such as Node.js/TypeScript, Java/Kotlin, Python, or Go.
• Familiarity with AI safety principles, responsible AI governance, and compliance models.

Key Skills

Education

Bachelor's degree