AIONOS

Generative AI Developer & Architect

AIONOS
Noida Not disclosed
2 hours ago
Hybrid
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About the job

Role: As a Generative AI Developer & Architect, you will be at the forefront of building the future of enterprise AI at AIonOS. This role demands a blend of expert GenAI implementation and technical leadership, where you will own the full lifecycle—from high-level solution architecture and RAG design to the delivery of scalable, production-ready AI platforms. You will act as a bridge between complex technical possibilities and measurable business outcomes, running feasibility workshops and rapid prototyping for global enterprise clients. Skills: The ideal candidate must possess a deep technical foundation in Python (Java is a plus) and a minimum of 2+ years of hands-on experience deploying complex RAG and GenAI solutions. The ideal candidates will be between 2 years to 12 years experience. You must be proficient in the Azure AI Foundry ecosystem (AWS/GCP is good to have) and have experience with advanced LLM orchestration (OpenAI, Anthropic, Mistral). Key competencies include expertise in Enterprise Workflow Automation, vector database management, LLMops, and agentic capabilities like Computer Use, all while maintaining a strong grasp of DevSecOps, observability, and AI scaling economics. Deliverables: Your primary focus will be designing and executing end-to-end RAG architectures and enterprise-grade automation workflows that integrate seamlessly into existing business processes. You are expected to deliver robust Proof of Concepts (POCs), technical feasibility reports, and comprehensive architectural blueprints (HLDs/LLDs) that address cost-performance trade-offs (TCO). Success in this role is defined by the successful deployment and scaling of secure, high-performance GenAI platforms that drive tangible transformation for enterprise partners.

Requirements

  • Python
  • Azure AI Foundry
  • Generative AI
  • RAG architectures

Preferred Technologies

  • Python
  • Azure AI Foundry
  • Generative AI
  • RAG architectures

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