AI Architect

Ascendion; New Jersey; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Ascendion is seeking an AI Engineer to design, build, and operate a secure, scalable AI infrastructure. You will implement cloud-native platforms on Azure, manage multi-agent orchestration, and deploy LLM integrations including Azure OpenAI.

The role emphasizes RAG pipelines, secure APIs, and robust observability. The ideal candidate has deep Azure expertise, 10+ years in AI/ML, and a strong DevOps/security mindset, with experience in LangGraph or Semantic Kernel.

Qualifications

• 10+ years in AI/ML roles, with senior engineering experience.
• Deep expertise in Azure services for AI platforms and production-grade pipelines.
• Strong understanding of LLMs, embeddings, RAG, and agentic architectures.
• Proficient in Python for orchestration and model development.
• Experience with infrastructure-as-code (Bicep, Terraform).
• Strong DevOps mindset and security practices for scalable systems.
• Familiarity with LangGraph, Semantic Kernel, AutoGen or similar frameworks.
• Knowledge of compliance and data governance for AI systems.

Responsibilities

• Architect and implement cloud-native AI platforms using Azure.
• Build and manage agent orchestration services (multi-agent workflows, tool invocation, state management).
• 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.

Skills

Azure AI Platform

LLMs & embeddings

Python

IaC (Bicep, Terraform)

DevOps & security

Agent frameworks (LangGraph, Semantic)

Compliance & data governance

Multi-agent orchestration

Cloud-native architecture

Tools

Azure Functions

App Services

Document Intelligence

Azure OpenAI

Azure AI Search

Terraform

Bicep

Job 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.