Full Stack Architect AI & Agentic Systems (ReactJS, NextJS, NodeJS)

TalentOla•Chicago, IL

5h•Hybrid

About The Position

We are seeking a highly experienced Full Stack Architect – AI & Agentic Systems to lead the design and implementation of next-generation digital platforms powered by modern web technologies and AI-driven architectures. The ideal candidate will possess deep expertise in ReactJS, NextJS, NodeJS, .NET Core, ASP.NET Web APIs, cloud-native application development, and enterprise architecture, along with hands-on experience designing and implementing Agentic AI solutions, Retrieval-Augmented Generation (RAG), AI orchestration frameworks, and AI Development Lifecycle (AI-DLC) practices. This role will drive the convergence of traditional software engineering and AI engineering, enabling scalable, secure, and production-ready AI-powered applications.

Requirements

ReactJS
NextJS
TypeScript
JavaScript (ES6+)
HTML5/CSS3
Redux / Redux Toolkit
Responsive & Accessible UI Design
NodeJS
ExpressJS
.NET Core (.NET 6+ / .NET 8)
ASP.NET Core Web API / REST API
C#
SQL Server
PostgreSQL
MongoDB
Vector Databases (Pinecone, Azure AI Search, Weaviate, Chroma, Milvus)
Microservices
API-First Design
Event-Driven Architecture
DDD
CQRS
SOLID Principles
Design Patterns
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
Azure / AWS
Docker
Kubernetes
Azure DevOps
GitHub Actions
Jenkins
Observability Platforms

Nice To Haves

Experience delivering AI-powered healthcare, payer, provider, or life sciences solutions.
Experience with Healthcare interoperability standards (FHIR, HL7).
AI Governance and Responsible AI experience.
Exposure to AI-driven SDLC transformation and engineering productivity platforms.
Experience implementing enterprise-scale Copilot or Agentic AI ecosystems.

Responsibilities

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.
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.
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.
Establish and operationalize AI-DLC processes across ideation, experimentation, development, deployment, monitoring, and continuous optimization.
Define standards for: Prompt Engineering, Context Engineering, Evaluation & Benchmarking, Model Selection, RAG Validation, Agent Testing, AI Security Reviews, Responsible AI Compliance.
Develop AI observability frameworks to monitor: Accuracy, Hallucinations, Latency, Token Consumption, Cost, User Satisfaction.
Implement AI release governance, validation gates, and production readiness assessments.
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.
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.