Job Title: .Net Full Stack Architect - AI & Agentic Systems (ReactJS, NextJS, NodeJS)
Location: Chicago, IL(Hybrid- 3 days/week in office)
Employment Type: Contract
Job Description:-
Key Responsibilities
Enterprise & Solution Architecture
Define end-to-end architecture for enterprise applications and AI-enabled platforms.
Design scalable systems leveraging microservices, API-first architecture, event-driven patterns, and cloud-native principles.
Establish architecture governance, design standards, and engineering best practices.
Conduct architecture reviews and technology assessments.
Full Stack Architecture
Architect modern frontend applications using ReactJS, NextJS, TypeScript, and component-driven design.
Design backend services using NodeJS, .NET Core, ASP.NET Web APIs, and microservices.
Define secure integration patterns across enterprise applications, cloud services, and AI platforms.
Drive performance optimization, observability, security, scalability, and maintainability.
Agentic AI Solution Architecture
Architect autonomous and semi-autonomous AI agents for business process automation.
Design multi-agent systems using orchestration frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
Define AI workflows involving planning, reasoning, memory management, tool usage, and human-in-the-loop controls.
Architect enterprise-grade RAG solutions integrating vector databases, enterprise knowledge sources, and LLMs.
Implement guardrails, AI governance, responsible AI controls, and evaluation frameworks.
AI Development Lifecycle (AI-DLC)
Establish and operationalize AI-DLC processes across ideation, experimentation, development, deployment, monitoring, and continuous optimization.
Define standards for:
o Prompt Engineering
o Context Engineering
o Evaluation & Benchmarking
o Model Selection
o RAG Validation
o Agent Testing
o AI Security Reviews
o Responsible AI Compliance
Develop AI observability frameworks to monitor:
o Accuracy
o Hallucinations
o Latency
o Token Consumption
o Cost
o User Satisfaction
Implement AI release governance, validation gates, and production readiness assessments.
Cloud, DevOps & MLOps
Architect solutions on Azure and/or AWS.
Design CI/CD pipelines supporting both software and AI workloads.
Integrate AI testing, prompt validation, and model evaluation into engineering workflows.
Establish MLOps/LLMOps practices for enterprise deployments.
Drive containerization and orchestration using Docker and Kubernetes.
Technical Leadership
Mentor architects, engineering leads, and AI engineers.
Drive AI-first engineering transformation initiatives.
Collaborate with business stakeholders to identify and prioritize AI opportunities.
Support solutioning, estimations, proposals, and executive presentations.
Required Technical Skills
Frontend
ReactJS
NextJS
TypeScript
JavaScript (ES6+)
HTML5/CSS3
Redux / Redux Toolkit
Responsive & Accessible UI Design
Backend
NodeJS
ExpressJS
.NET Core (.NET 6+ / .NET 8)
ASP.NET Core
Web API / REST API
C#
Databases
SQL Server
PostgreSQL
MongoDB
Vector Databases (Pinecone, Azure AI Search, Weaviate, Chroma, Milvus)
Architecture
Microservices
API-First Design
Event-Driven Architecture
DDD
CQRS
SOLID Principles
Design Patterns
AI & Agentic AI
Azure OpenAI / OpenAI / Anthropic / Gemini
RAG Architecture
Agentic Workflows
Multi-Agent Systems
Semantic Kernel
LangChain / LangGraph
MCP (Model Context Protocol)
AI Guardrails
Prompt Engineering
Context Engineering
AI Evaluation Frameworks
Cloud & DevOps
Azure / AWS
Docker
Kubernetes
Azure DevOps
GitHub Actions
Jenkins
Observability Platforms
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