Agentic AI & Copilot Architect

Role Summary You will design and deliver enterprise-grade Agentic AI and Copilot solutions. Your primary focus is on Microsofts AI stack (Microsoft 365 Copilot, Copilot Studio, Azure OpenAI, Fabric, Power Platform), but youll also apply your knowledge of other vendor frameworksGoogle Vertex A2A, AWS AI services (SageMaker, Bedrock), and ServiceNow Agentforceto meet diverse client needs. Youll own handson prototyping, architecture, and production deployments that embed intelligent agents into real business processes. Key Responsibilities Solution Architecture Define end-to-end Copilot and Agentic AI frameworks on Microsoft 365, Azure AI, Fabric, and Power Platform. Design connectors and data flows between LLM-powered agents and enterprise systems (CRM, ticketing, document workflows). Incorporate alternative agent frameworksGoogle Vertex A2A, AWS SageMaker/Bedrock, ServiceNow Agentforceas fitting for client requirements. Hands-On Delivery Build and optimize PoCs: write code artifacts, refine model performance, and create deployment scripts. Implement retrieval-augmented generation pipelines and GenAIOps best practices for monitoring, versioning, and automated retraining. Mentor engineering teams on LLM integration, fine-tuning, RAG techniques, and CI/CD pipelines. Vendor Collaboration & Governance Engage with Microsoft, OpenAI, Google, AWS, and ServiceNow product teams to align on prerequisites and feature roadmaps. Establish security, compliance, and ethical-AI guardrails spanning all platforms. Client Engagement & Impact Measurement Partner with client IT and change-management teams to embed agents smoothly into production workflows. Define metrics and collect telemetry to measure usage, accuracy, and business value; drive iterative improvements. Minimum Qualifications Experience: 8+ years in enterprise AI/ML architecture or software engineering, delivering Copilot-style or agentic AI solutions. Microsoft Stack: Deep hands-on expertise with Microsoft 365 Copilot, Copilot Studio, Azure Cognitive Services, Azure OpenAI Service, Fabric, and Power Platform. Multi-Vendor Awareness: Familiarity with Google Vertex A2A, AWS AI services (SageMaker, Bedrock), and ServiceNow Agentforce. Core Skills: Proficiency in Python and frameworks (PyTorch, TensorFlow); strong understanding of retrieval-augmented generation and MLOps pipelines. Communication: Excellent stakeholder-management and presentation skills, with experience advising technical and executive audiences. Preferred Qualifications Certifications: Azure Solutions Architect Expert, Azure AI Engineer Associate, GCP Professional ML Engineer, AWS Certified ML Specialist, or ServiceNow credentials. DevOps Practices: Hands-on experience with CI/CD, infrastructure-as-code (Terraform, Azure DevOps, AWS CloudFormation). Consulting/CoE Experience: Prior roles in AI Center of Excellence or consulting environments, driving multiple client engagements. Behavioural Competencies Strategic Mindset: Translate complex technical options into clear business value propositions. Collaborative Partner: Work effectively with global, cross-functional teams and vendor architects. Thought Leadership: Confident presenting at industry events and contributing technical content on agentic AI. Data-Driven: Focus relentlessly on metrics, telemetry, and iterative improvements.