RAVIN IT SOLUTIONS, Inc

RAVIN IT SOLUTIONS, Inc

.Net Backend AI Architet

Reston, Virginia, USA · Contract

Sponsorship not specifiedDetected 64 days ago
TypeScriptPythonJavaKotlinNode.js.NETDistributed SystemsSQLNoSQLAWSGCPAzureCloud PlatformsCI/CDSite Reliability EngineeringPlatform EngineeringAPI DevelopmentKafkaMachine LearningData ScienceLLMsRAGAgentic AICybersecurity

About the role

  • .NET Backend AI Architect Job Overview Core Back End Architecture • Strong experience architecting scalable, secure, and observable distributed systems, including microservices and event driven architectures. • Proven expertise defining service architecture strategies, including APIs, data contracts, and runtime platforms across multiple teams. • Deep
  • understanding of system design fundamentals such as consistency models, caching strategies, resilience patterns, and fault tolerance. • Hands on experience with at least one major backend ecosystem: Node.js/TypeScript, Java/Kotlin,.NET, Python, or Go. • Strong background in operational excellence, including observability, performance tuning, incident

Responsibilities

  • Deep understanding of system design fundamentals such as consistency models, caching strategies, resilience patterns, and fault tolerance.
  • Experience integrating or developing with LLMs and Generative AI services within enterprise platforms.
  • Ability to design intelligent service flows, including Retrieval Augmented Generation (RAG) and agent based architectures.
  • Experience developing AI powered platform components, such as intelligent API gateways, policy engines, or observability assistants.
  • Solid grounding in security fundamentals, including threat modeling, identity, encryption, and secure by default design patterns Roles & Responsibilities Back End Architecture Leadership
  • Architect and design enterprise scale backend platforms that are secure, highly available, performant, and cost efficient.
  • Define and implement AI augmented backend architectures, including inference aware service patterns and model serving strategies.
  • Partner with Data Science, ML Engineering, and Product teams to operationalize models with strong SLAs, security, and cost controls.
  • Promote observability first design using logs, metrics, traces, and AI assisted insights.
  • Back End Architect, Distributed Systems, Microservices, Event Driven Architecture, API Design, Cloud Native, AWS, DevEx, CI/CD, Observability, LLM, GenAI, RAG, AI Agents, Inference Architecture, Platform Engineering

Requirements

  • Strong understanding of prompt engineering, evaluation techniques, and AI quality metrics.
  • Experience with cloud platforms ( AWS preferred; Azure/Google Cloud Platform acceptable).
  • Strong understanding of API gateways, service mesh, and networking fundamentals.
  • Hands on experience with data and streaming technologies such as SQL, NoSQL, Kafka, and Redis.
  • Experience with CI/CD pipelines, infrastructure as code, automated testing, and progressive delivery strategies.

Benefits

  • Knowledge of AI driven analytics and telemetry for monitoring model performance and service health.
  • Drive technical decisions that balance innovation, maintainability, operability, and long term platform health.
  • Ability to balance strategic vision with hands-on architectural depth.
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