Custom .NET and Azure software development with emerging agentic AI work
Aezion is a Frisco-based custom software shop whose core stack is Microsoft-centric (C#, ASP.NET MVC, Entity Framework, SQL Server, Azure), extended with event-driven tooling like Kafka, RabbitMQ and Azure Event Hubs. Recent job posts point to a push into multi-agent AI, LangGraph workflows and natural language query systems, with delivery capacity being built out in India under senior and lead engineering hires, including a .NET lead.
Notable leadership hires: Dot Net Lead
Aezion, Inc is a privately held software services company founded in 2012 and headquartered in Frisco, Texas, with 51–200 employees. It delivers custom software end to end, covering architecture, design, development, hosting, deployment and ongoing support. Service lines include web and mobile applications, software product development, QA and testing, dedicated development teams, business intelligence and analytics, and digital marketing. Healthcare is a named focus area, and the company serves clients in the Dallas–Fort Worth region.
Aezion builds primarily on C#, .NET, ASP.NET MVC, Entity Framework and SQL Server on Azure, plus Kafka, RabbitMQ, Docker, Kubernetes, Prometheus, Grafana, Elasticsearch, GraphQL and Python, with AWS and GCP also in use.
Current hiring is concentrated in India, led by engineering with senior and lead roles such as a .NET lead, alongside product, sales and healthcare positions. Hiring velocity is accelerating.
Yes. Job posts reference multi-agent AI system architecture, intelligent workflows built with LangGraph, and enterprise natural language query systems, along with governance and observability for AI agents.
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Aezion, Inc's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.