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
✅