DOTNET AI Architect

Job Overview:

Pay Range: $47hr - $52hr

Requirement/Must Have:

• 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.) and 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.

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.

Nice to Have:

• 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.

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.

• Medical, Dental, and Vision Insurance
• 401(k) Retirement Plan
• Health Savings Account (HSA)
• Disability Insurance (Short-Term and Long-Term)
• Life and AD&D Insurance
• Paid Sick Leave (where required by applicable state or local law)
• Supplemental Insurance Plans
• Identity Theft Protection
• Pet Insurance
• Employee Wellness Programs
• Employee Assistance Program (EAP)
• Career Growth and Professional Development Opportunities