Principal Agentic AI Architect

About SIDGS:

SID Global Solutions is a premier AI-first digital transformation company, delivering intelligent full-stack solutions and services worldwide. We specialize in embedding AI across the enterprise to accelerate transformation, modernize technology, and unlock new revenue streams. Our core expertise spans AI-powered modernization, cloud and infrastructure solutions, application innovation, and advanced data analytics. As a leading Google Apigee implementation partner, we also bring you SAMi-Smart API Monetization Platform is our flagship platform for API management. With a global footprint and 1000+ professionals, SID Global Solutions is committed to building a smarter, AI-driven future through innovation and impact.

Role: Principal Agentic AI Architect | Enterprise AI Platforms, GenAI, Multi-Agent Systems & Full Stack AI Solutions

Location: Exton, PA (Onsite)
Employment Type: Full-Time
Company: SID Global Solutions

Transform the Future of Enterprise AI

SID Global Solutions is seeking a highly accomplished, hands-on technology leader to help build the next generation of Enterprise AI Platforms, Agentic AI Solutions, AI-Powered Applications, Intelligent Automation Platforms, and Industry-Specific AI Products.

We are looking for a leader with deep expertise in:

• Agentic AI
  
• Generative AI (GenAI)
  
• Multi-Agent Systems
  
• Large Language Models (LLMs)
  
• Retrieval Augmented Generation (RAG)
  
• Enterprise AI Platforms
  
• AI Copilots
  
• Intelligent Assistants
  
• AI-Powered Workflow Automation
  
• Full Stack Enterprise Application Development
  
• Enterprise Architecture
  
• Cloud-Native Engineering
  

This role combines AI Architecture, Enterprise Solution Architecture, Full Stack Engineering, Product Development, Customer Consulting, Pre-Sales Solutioning, Innovation Leadership, and AI Practice Development.

You will be responsible for building complete AI-powered business solutions that span user experience, application services, AI orchestration layers, enterprise integrations, governance frameworks, and cloud-native deployments.

This position offers a significant career growth path into AI Practice Leadership, helping shape SID Global's long-term AI platform strategy, reusable agent ecosystem, enterprise solution offerings, and AI-driven business transformation initiatives.

What You'll Do

Agentic AI Architecture & Engineering

• Design and develop enterprise-scale Agentic AI and Generative AI platforms.
  
• Architect and implement AI Agents, Multi-Agent Systems, Autonomous Agents, AI Copilots, Intelligent Assistants, and Agentic Workflow Applications.
  
• Design and implement solutions using:
  
• • LangChain
    
  • LangGraph
    
  • AutoGen
    
  • CrewAI
    
  • Agent Development Kit (ADK)
    
  • Model Context Protocol (MCP)
    
  • AI Agent Frameworks
    
  • Agent Communication Protocols
    
  • Agent Workflow Engines
    
• Design agent workflows, memory architectures, planning strategies, tool integrations, state management frameworks, and agent collaboration models.
  
• Build reusable AI agents, SDKs, frameworks, accelerators, reference architectures, and platform capabilities.
  
• Develop enterprise-scale Retrieval Augmented Generation (RAG) platforms leveraging semantic search, vector databases, embeddings, and enterprise knowledge systems.
  
• Design enterprise search platforms, AI knowledge bases, knowledge graphs, metadata frameworks, and content intelligence architectures.
  
• Build AI-powered decision support systems, intelligent workflow solutions, and business process automation capabilities.
  
• Design Human-in-the-Loop AI systems, approval workflows, escalation mechanisms, and responsible AI control frameworks.
  
• Lead development of intelligent automation solutions that transform business operations and enterprise workflows.
  

 Full Stack AI-Powered Enterprise Application Development

• Design and develop end-to-end AI-powered enterprise applications from user experience through production deployment.
  
• Build enterprise software solutions including:
  
• • AI Workbenches
    
  • Enterprise Portals
    
  • Customer-Facing Applications
    
  • SaaS Platforms
    
  • Workflow Automation Platforms
    
  • Knowledge Management Systems
    
  • Digital Experience Platforms
    
  • Operational Dashboards
    
  • AI-Powered Business Applications
    
• Architect complete application ecosystems spanning:
  
• • Front-End Applications
    
  • Backend Services
    
  • APIs
    
  • Agent Orchestration Layers
    
  • Enterprise Integrations
    
  • Security Frameworks
    
  • Data Platforms
    
  • Cloud Infrastructure
    
• Develop reusable user interface components, services, APIs, integration frameworks, and platform accelerators.
  
• Integrate AI capabilities into customer-facing applications, enterprise systems, and operational workflows.
  
• Implement scalable, resilient, secure, and maintainable enterprise application architectures.
  
• Lead application modernization initiatives that embed AI into existing enterprise systems and business processes.
  

Enterprise Architecture & Solution Design

• Define enterprise reference architectures, design standards, reusable patterns, and implementation frameworks.
  
• Architect end-to-end enterprise solutions spanning:
  
• • AI Platforms
    
  • Enterprise Applications
    
  • Integration Layers
    
  • Data Platforms
    
  • Security Architectures
    
  • Cloud Infrastructure
    
• Design AI-powered enterprise architecture patterns for intelligent automation and digital transformation.
  
• Develop enterprise integration strategies connecting AI solutions with internal and external business systems.
  
• Design application modernization strategies leveraging AI, automation, and cloud-native technologies.
  
• Establish architecture governance processes, technology standards, and engineering excellence practices.
  

AI Operations, Governance & Platform Engineering

• Establish AgentOps, MLOps, LLMOps, DevSecOps, AI Observability, and lifecycle management frameworks.
  
• Implement Responsible AI, AI Governance, AI Safety, AI Guardrails, and Enterprise Security controls.
  
• Define AI reliability, monitoring, tracing, benchmarking, evaluation, and operational excellence frameworks.
  
• Design and implement:
  
• • AI Monitoring
    
  • Prompt Monitoring
    
  • Model Monitoring
    
  • Distributed Tracing
    
  • Observability Platforms
    
  • Performance Analytics
    
• Develop automated testing frameworks for:
  
• • AI Agents
    
  • Multi-Agent Systems
    
  • RAG Applications
    
  • Prompt Engineering
    
  • Retrieval Testing
    
  • Regression Testing
    
  • Guardrail Validation
    
  • AI Evaluation
    
• Define quality metrics for:
  
• • Accuracy
    
  • Groundedness
    
  • Retrieval Quality
    
  • User Experience
    
  • Reliability
    
  • Latency
    
  • Business Outcomes
    
  • Operational Efficiency
    
• Optimize AI systems for scalability, reliability, maintainability, security, and cost effectiveness.
  

 Customer Consulting & Business Transformation

• Lead executive workshops, AI strategy sessions, architecture reviews, design-thinking initiatives, and innovation engagements.
  
• Identify enterprise AI transformation opportunities across business functions and industries.
  
• Translate complex business challenges into scalable AI-powered solutions.
  
• Serve as a trusted advisor to customers and executive stakeholders.
  
• Support enterprise AI adoption programs, digital transformation initiatives, and intelligent automation strategies.
  
• Drive business process transformation through AI-powered workflow automation and decision intelligence platforms.
  

Pre-Sales, Solutioning & Innovation

• Support proposal development, RFP responses, estimates, architecture recommendations, and technical solution design.
  
• Participate in proof-of-concepts, innovation programs, demonstrations, executive briefings, and customer presentations.
  
• Collaborate with Sales, Alliances, Business Development, and Delivery teams to develop new AI opportunities.
  
• Create reusable solution offerings, accelerators, reference architectures, and industry-specific AI frameworks.
  
• Contribute to product strategy, AI platform evolution, and next-generation AI service offerings.
  

Leadership & AI Practice Development

• Lead architecture reviews, design governance, and engineering excellence initiatives.
  
• Mentor AI engineers, architects, developers, and technology leaders.
  
• Support hiring, capability development, technical enablement, and organizational growth.
  
• Establish AI engineering standards, delivery methodologies, and architectural best practices.
  
• Drive innovation, research, thought leadership, and market differentiation.
  
• Help shape the long-term strategy, vision, and growth roadmap for SID Global's AI Practice.
  

Required Qualifications

Professional Experience

• 10+ years of software engineering experience.
  
• 4+ years designing and delivering AI, Generative AI, Machine Learning, or Agentic AI solutions in production environments.
  
• Proven experience architecture and delivering enterprise-scale AI-powered applications and platforms.
  
• Demonstrated success leading enterprise architecture and complex technology initiatives.
  

Agentic AI, GenAI & LLM Engineering

Hands-on experience with:

• LangChain
  
• LangGraph
  
• AutoGen
  
• CrewAI
  
• Agent Development Kit (ADK)
  
• Model Context Protocol (MCP)
  
• AI Agent Frameworks
  
• Multi-Agent Architectures
  
• Agent Communication Protocols
  
• AI Copilot Architecture
  
• Agentic Workflow Solutions
  

Experience delivering:

• Retrieval Augmented Generation (RAG)
  
• Enterprise Search
  
• Semantic Search
  
• Enterprise Knowledge Systems
  
• AI Knowledge Bases
  
• Intelligent Assistants
  
• AI Copilots
  
• LLM Applications
  
• Autonomous Agent Solutions
  
• Intelligent Automation Platforms 
  

Large Language Models & AI Platforms

Experience with modern LLM ecosystems including one or more of the following:

• OpenAI
  
• Azure OpenAI
  
• Gemini
  
• Claude
  
• Anthropic
  
• Mistral
  
• Llama
  
• Hugging Face
  
• Vertex AI
  
• Azure AI Foundry
  
• Amazon Bedrock
  

Experience with:

• Prompt Engineering
  
• Prompt Management
  
• Retrieval Engineering
  
• Grounded AI Systems
  
• AI Evaluation
  
• AI Safety
  
• Responsible AI
  
• AI Governance
  
• LLMOps
  

Full Stack Application Development

Strong experience building enterprise-grade software applications and SaaS platforms.

Front-End Development

Experience with:

• React
  
• ReactJS
  
• Next.js
  
• Angular
  
• TypeScript
  
• JavaScript
  
• HTML5
  
• CSS3
  
• Tailwind CSS
  
• Material UI
  

Backend Development

Experience with:

• Python
  
• FastAPI
  
• Flask
  
• Node.js
  
• Express.js
  
• Java
  
• Spring Boot
  
• .NET Core
  
• REST APIs
  
• GraphQL
  

Enterprise Application Engineering

Experience building:

• Enterprise Applications
  
• SaaS Platforms
  
• Workflow Automation Solutions
  
• Business Process Automation Platforms
  
• Enterprise Portals
  
• Microservices Architectures
  
• Event-Driven Architectures
  
• Distributed Systems
  
• Integration Platforms
  

Experience implementing:

• Authentication
  
• Authorization
  
• Single Sign-On (SSO)
  
• Role-Based Access Control (RBAC)
  
• API Security
  
• Enterprise Identity Management 
  

Data, Knowledge & Search Architecture

Experience with:

Vector Databases

• Pinecone
  
• Weaviate
  
• Chroma
  
• FAISS
  
• Azure AI Search
  

Enterprise Search & Knowledge Systems

• Enterprise Search
  
• Semantic Search
  
• Knowledge Graphs
  
• Enterprise Knowledge Management
  
• Metadata Management
  
• Information Retrieval
  
• Content Intelligence
  

Data Platforms

• BigQuery
  
• Apache Spark
  
• Kafka
  
• Airflow
  
• Data Pipelines
  
• ETL / ELT
  
• Data Lakes
  
• Data Warehousing
  

Databases

• PostgreSQL
  
• MySQL
  
• SQL Server
  
• MongoDB
  
• Redis
  
• Cosmos DB 
  

Cloud & Platform Engineering

Experience deploying enterprise AI and business applications on at least one major public cloud platform:

• Microsoft Azure
  
• Amazon Web Services (AWS)
  
• Google Cloud Platform (GCP)
  

Experience with:

• Docker
  
• Kubernetes
  
• CI/CD
  
• Infrastructure Automation
  
• Monitoring Platforms
  
• Observability Platforms
  
• Platform Engineering 
  

Enterprise Architecture & Operations

Strong understanding of:

• Enterprise Architecture
  
• Solution Architecture
  
• Cloud Architecture
  
• AI Governance
  
• Responsible AI
  
• AgentOps
  
• MLOps
  
• LLMOps
  
• DevSecOps
  
• Application Security
  
• Reliability Engineering
  
• Scalability Engineering
  
• Performance Engineering
  
• Enterprise Integration Patterns 
  

Preferred Qualifications

Google Cloud Platform (Highly Preferred)

Experience with:

• Vertex AI
  
• Gemini
  
• Agent Development Kit (ADK)
  
• Cloud Run
  
• BigQuery
  
• Google Kubernetes Engine (GKE)
  
• Cloud Functions
  
• Pub/Sub
  
• Apigee
  
• Cloud-Native AI Services 
  

Azure Experience

• Azure AI Foundry
  
• Azure OpenAI
  
• Azure AI Search
  
• Azure Functions
  
• Azure Kubernetes Service (AKS) 
  

AWS Experience

• Amazon Bedrock
  
• ECS
  
• EKS
  
• Lambda 
  

Industry Experience

Experience delivering AI-powered solutions in:

• Banking
  
• Financial Services
  
• Insurance
  
• Healthcare
  
• Public Sector
  
• Government
  
• Contact Centers
  
• Customer Service
  
• Human Resources
  
• Talent Acquisition
  
• Supply Chain
  
• Enterprise Operations 
  

Advanced AI & Product Engineering

Experience with:

• AI Evaluation Frameworks
  
• AI Testing Methodologies
  
• Machine Learning Engineering
  
• Predictive Analytics
  
• Recommendation Systems
  
• Classification Models
  
• AI Beyond LLMs
  

Experience building:

• Enterprise AI Products
  
• Customer-Facing Platforms
  
• Digital Products
  
• Agent Workbenches
  
• Knowledge Portals
  
• Workflow Automation Solutions
  
• AI-Powered SaaS Platforms 
  

What Success Looks Like

The successful candidate will:

Architect enterprise-scale Agentic AI platforms and Multi-Agent Systems

Deliver AI-powered enterprise applications from user experience through production operations

Build reusable AI agents, frameworks, accelerators, and platform capabilities

Establish engineering, governance, observability, and operational excellence standards