.NET AI Architect- W2 Candidates Only

Key Responsibilities 

Design, develop, and deploy AI-enabled applications and intelligent automation solutions. 

Build and optimize applications that leverage Large Language Models (LLMs) and agentic AI workflows. 

Develop scalable backend services and APIs using .NET/C# (preferred) or Java. 

Design and implement Retrieval-Augmented Generation (RAG) architectures for knowledge-driven AI solutions. 

Integrate structured and unstructured data sources, including document repositories and enterprise content systems. 

Work with relational and non-relational databases to support AI and analytics-driven applications. 

Develop and maintain document processing, vector search, and knowledge retrieval capabilities. 

Collaborate with data, analytics, and business teams to identify automation opportunities and AI use cases. 

Create technical solution designs, architecture documentation, and implementation plans. 

Ensure scalability, security, performance, and governance standards are incorporated into all solutions. 

Evaluate emerging AI technologies and recommend best practices for enterprise adoption. 

 

Required Qualifications 

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent practical experience. 

5+ years of software development experience. 

Hands-on experience working with Large Language Models (LLMs) and AI application development. 

Experience designing and implementing agentic AI workflows and intelligent automation solutions. 

Strong object-oriented programming skills. 

Proficiency in C#/.NET (preferred) or Java. 

Solid understanding of software architecture, design patterns, and application development best practices. 

Experience with both:  

Relational databases (SQL Server, PostgreSQL, Oracle, etc.) 

Non-relational/document databases (MongoDB, Cosmos DB, DynamoDB, etc.) 

Understanding of Retrieval-Augmented Generation (RAG) concepts and architectures. 

Experience working with unstructured data, document repositories, and content processing solutions. 

Knowledge of REST APIs, microservices, and cloud-based application development. 

Strong analytical, troubleshooting, and problem-solving abilities. 

 

Preferred Qualifications 

Experience with Azure AI, Azure OpenAI, AWS AI/ML, or Google Cloud AI services. 

Familiarity with vector databases and semantic search technologies. 

Experience with prompt engineering, model orchestration frameworks, and AI agents. 

Exposure to data engineering, analytics, and business intelligence solutions. 

Experience working in Agile/Scrum environments. 

Knowledge of enterprise integration patterns and automation platforms. 

Experience with DevOps practices, CI/CD pipelines, and cloud-native architectures. 

 

Technical Skills 

AI & Automation 

Large Language Models (LLMs) 

Agentic AI Frameworks 

Retrieval-Augmented Generation (RAG) 

Prompt Engineering 

Semantic Search & Knowledge Retrieval 

Intelligent Automation 

Development 

C# / .NET (Preferred) 

Java 

Object-Oriented Design 

REST APIs 

Microservices Architecture 

Data Platforms 

SQL Server, PostgreSQL, Oracle 

MongoDB, Cosmos DB, DynamoDB 

Document Databases 

Unstructured Data Processing 

Data Analytics Platforms 

Cloud & Tools 

Microsoft Azure (Preferred) 

Azure OpenAI Services 

Git/GitHub/Azure DevOps 

CI/CD Pipelines 

Agile Development Practices