8–12 years of progressive experience in solution architecture, technical architecture, or senior engineering roles within IT services or consulting organizations.
Hands-on experience designing and delivering solutions across AI/ML, cloud platforms, data engineering, and application modernization.
Prior experience at an IT services company, digital engineering firm, or consulting organization is strongly preferred.
AI & GenAI: Working knowledge of Generative AI, LLMs, Agentic AI frameworks (LangChain, LangGraph, AutoGen), RAG architectures, and vector databases.
Cloud: Solid hands-on experience with AWS, Azure, or GCP; cloud-native design patterns, Kubernetes, DevSecOps, and CI/CD pipelines.
Engineering Stack: Strong proficiency in .NET (C#, ASP.NET Core) and/or OpenSource stacks (Java, Python, Node.js); experience with both is a significant advantage.
Intelligent Automation: Experience with RPA tools, workflow automation, and AI-augmented process automation.
Enterprise Platforms: Familiarity with Oracle, SAP, Salesforce, or ServiceNow is a plus.
AI & GenAI: Working knowledge of Generative AI, LLMs, Agentic AI frameworks (LangChain, LangGraph, AutoGen), RAG architectures, and vector databases.
Cloud: Solid hands-on experience with AWS, Azure, or GCP; cloud-native design patterns, Kubernetes, DevSecOps, and CI/CD pipelines.
Engineering Stack: Strong proficiency in .NET (C#, ASP.NET Core) and/or OpenSource stacks (Java, Python, Node.js); experience with both is a significant advantage.
Intelligent Automation: Experience with RPA tools, workflow automation, and AI-augmented process automation.
Enterprise Platforms: Familiarity with Oracle, SAP, Salesforce, or ServiceNow is a plus.
