Senior AI Architect

We are looking for a Senior AI Architect to lead the design, architecture, and implementation of enterprise-grade AI automation solutions using Generative AI, Large Language Models (LLMs), and Agentic AI. The ideal candidate will work closely with business stakeholders and clients to understand business challenges, define AI strategies, design scalable solution architectures, and deliver production-ready AI systems.

This role requires deep expertise in the AI Development Lifecycle (AI-DLC), AI orchestration frameworks, Retrieval-Augmented Generation (RAG), enterprise integrations, and cloud AI platforms. The successful candidate will serve as a trusted technical advisor from solution discovery through implementation and production deployment.

• Architect and deliver end-to-end AI automation solutions for enterprise business processes.
  

• Design and implement Agentic AI and multi-agent systems capable of planning, reasoning, task execution, and collaboration.
  

• Lead the complete AI Development Lifecycle (AI-DLC), including solution design, data preparation, model evaluation, deployment, monitoring, governance, and continuous optimization.
  

• Design and develop AI assistants and autonomous agents integrated with enterprise applications, APIs, databases, and business workflows.
  

• Build Retrieval-Augmented Generation (RAG) solutions using vector databases, embeddings, and enterprise knowledge repositories.
  

• Design AI-driven workflow orchestration for business functions such as Customer Support, IT Operations, HR, Finance, Sales, Procurement, and Business Process Automation.
  

• Define secure AI architectures with governance, guardrails, auditability, compliance, and Human-in-the-Loop (HITL) workflows.
  

• Evaluate and recommend appropriate foundation models (OpenAI, Anthropic Claude, Gemini, Llama, Mistral, etc.) based on technical and business requirements.
  

• Collaborate with business and technology stakeholders to identify automation opportunities and translate them into scalable AI solutions.
  

• Drive reusable AI frameworks, architecture standards, and best practices across enterprise automation initiatives.
  

• Provide technical leadership through client workshops, architecture reviews, executive presentations, and solution design sessions.
  

• Mentor engineering teams and guide AI solution implementation from concept to production.
  

• Strong expertise in Large Language Models (LLMs) and Generative AI.
  

• Deep understanding of the AI Development Lifecycle (AI-DLC).
  

• Experience designing Agentic AI and Multi-Agent Architectures.
  

• Expertise in Retrieval-Augmented Generation (RAG).
  

• Strong knowledge of Prompt Engineering and Context Engineering.
  

• AI Planning, Reasoning, Memory Management, and State Management.
  

• Human-in-the-Loop (HITL) workflows.
  

• AI Governance, Responsible AI, and AI Security.
  

Hands-on experience with one or more of:

• LangChain
  

• LangGraph
  

• LlamaIndex
  

• Semantic Kernel
  

• CrewAI
  

• AutoGen
  

• AI Agent Orchestration Frameworks
  

• Microsoft Power Automate / RPA
  

• Microsoft Copilot Studio (Preferred)
  

• Azure AI Foundry
  

• AI-native workflow orchestration platforms
  

• API-first integration architectures
  

• REST APIs
  

• Webhooks
  

• MCP
  

• Enterprise system integration
  

Experience with one or more:

• Azure OpenAI
  

• Azure AI Foundry
  

• AWS Bedrock
  

• Google Vertex AI
  

• Azure Functions
  

• Azure Logic Apps
  

• Equivalent serverless cloud services
  

• Python and/or .NET
  

• SQL
  

• Git
  

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related discipline.
  

• 8+ years of experience in Software Engineering, Solution Architecture, or Enterprise Architecture.
  

• 3+ years of hands-on experience designing and deploying production-grade Generative AI and LLM solutions.
  

• Experience implementing enterprise automation solutions using AI and RPA technologies.
  

• Strong client-facing consulting experience, including workshops, solution architecture, and executive presentations.
  

• Experience deploying AI applications with monitoring, observability, governance, and security controls.
  

• Relevant Cloud, AI, or Solution Architecture certifications are preferred.
  

• Enterprise AI automation strategy and architecture.
  

• Production-ready autonomous AI agents for enterprise workflows.
  

• Intelligent workflow automation to improve operational efficiency.
  

• Reusable AI platforms, services, and architectural standards.
  

• Secure, scalable, governed, and measurable AI solutions delivering tangible business value.
  

• AI Solution Architecture
  

• Enterprise Automation
  

• Generative AI & LLMs
  

• Agentic AI & Multi-Agent Systems
  

• Retrieval-Augmented Generation (RAG)
  

• AI Governance & Responsible AI
  

• Cloud AI Platforms
  

• Workflow Orchestration
  

• Enterprise Integration
  

• Client Consulting & Stakeholder Management
  

• Technical Leadership & Mentorship
  

• Strategic Problem Solving