Ascendion
AI Architect
- Compensation
- Not disclosed
- Location
- Remote
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Architecture
- Posted
Skills
Must have
- 10+ years in AI, ML - AI Engineer.
- Deep expertise in Azure (Functions, App Services, Document Intelligence, AI Search, OpenAI).
- Strong understanding of LLMs, embeddings, RAG, and agentic architectures.
- Proficiency in Python.
- Experience with infrastructure-as-code (Bicep, Terraform).
- Strong DevOps and security mindset.
- Experience with LangGraph, Semantic Kernel, AutoGen, or similar agent frameworks.
- Knowledge of compliance and data governance for AI systems.
Full description
The AI Engineer designs, builds, and operates the core infrastructure and orchestration backbone of AI solutions. This role ensures the platform is secure, scalable, resilient, and production-grade.
Responsibilities:
- Architect and implement cloud-native AI platforms using Azure.
- Build and manage agent orchestration services (multi-agent workflows, tool invocation, state management).
- Knowledge in MCP, A2A, and other new protocols
- Deploy and manage LLM integrations (Azure OpenAI, embeddings, fine-tuned models).
- Implement RAG pipelines using Azure AI Search, vector databases, and storage.
- Design secure APIs, authentication, authorization, and secrets management.
- Support observability: logging, tracing, metrics, and AI performance dashboards.
Requirements:
- 10+ years in AI, ML - AI Engineer.
- Deep expertise in Azure (Functions, App Services, Document Intelligence, AI Search, OpenAI).
- Strong understanding of LLMs, embeddings, RAG, and agentic architectures.
- Proficiency in Python.
- Experience with infrastructure-as-code (Bicep, Terraform).
- Strong DevOps and security mindset.
- Experience with LangGraph, Semantic Kernel, AutoGen, or similar agent frameworks.
- Knowledge of compliance and data governance for AI systems.