Copilot Studio SME

<h2><b>Role Summary</b></h2><br /><p>Avanade India’s Data &amp; AI practice is looking for an Agentic AI &amp; Copilot Studio SME to lead client enablement and adoption for agent-based AI solutions built on Microsoft Copilot Studio and the wider Microsoft agent ecosystem. This is a training-led, client-facing role: the primary focus is designing and delivering structured skilling — instructor-led workshops, hands-on labs, train-the-trainer programmes and champion communities — for large organisations building and scaling agents.</p><br /><p>What distinguishes this role from a platform-training role is agentic depth. You are expected to understand how agents actually work — orchestration and reasoning loops, tool and function calling, grounding and retrieval, memory and context handling, multi-agent patterns, evaluation and guardrails — and to teach Copilot Studio in that context rather than as a feature tour. You will build reference agents yourself, advise on live engagements, and be the person client teams escalate hard agent-design questions to.</p><br /><h2><b>Key Responsibilities</b></h2><br /><ul><li>Own the design and delivery of agentic AI and Copilot Studio skilling programmes for large enterprise audiences — curriculum design, instructor-led sessions, hands-on labs, self-paced content, assessments and certification pathways.</li><li>Run train-the-trainer and champion-enablement programmes so client teams can sustain and scale agent development independently after the engagement.</li><li>Teach agent design as a discipline, not a tool walkthrough — task decomposition, orchestration and reasoning patterns, tool/action design, grounding strategy, memory and context, human-in-the-loop checkpoints, failure modes and cost/latency trade-offs.</li><li>Tailor content and depth to distinct audiences — business makers, pro-code engineering teams, and business and IT leadership.</li><li>Build reference and demo agents in Copilot Studio — topics, generative answers, actions and connectors, agent flows, knowledge sources and multi-agent handoffs — to anchor training and seed client use cases.</li><li>Design and maintain lab environments, sandbox tenants and exercise sets, keeping them current with the fast-moving agent-platform roadmap.</li><li>Provide hands-on advisory on live engagements: agent design reviews, grounding and knowledge-source guidance, action/connector patterns, prompt and instruction design, testing and evaluation approaches, and go-live readiness.</li><li>Advise on when to build in Copilot Studio versus a pro-code approach on Azure AI Foundry or an agent framework — and how the two coexist in a single client landscape.</li><li>Establish evaluation and Responsible AI practice for agents: test sets and regression suites, groundedness and quality measurement, content safety, guardrails, human oversight and monitoring in production.</li><li>Advise clients on agent governance and operating models — environment strategy, DLP policies, maker onboarding, publishing and approval workflows, agent lifecycle management, licensing considerations and usage analytics.</li><li>Support use-case discovery workshops — identifying, qualifying and prioritising agent scenarios, and setting realistic expectations on what agents can and cannot do reliably.</li><li>Act as the practice reference point for agentic AI enablement: build reusable training assets, playbooks, agent templates and accelerators, and mentor consultants joining the capability.</li><li>Contribute to presales as the subject-matter expert — enablement approach, effort and duration estimates, demos and client-facing solution walkthroughs.</li></ul><h2></h2>

<h2><b>Required Skills &amp; Experience</b></h2><br /><ul><li>9–12 years of overall experience in software engineering, automation, data or AI roles, with a recent and substantial focus on generative and agentic AI.</li><li>Hands-on experience designing and building agentic AI solutions — multi-step orchestration, tool and function calling, retrieval and grounding, memory and context management, and multi-agent collaboration patterns.</li><li>Up to 2 years of hands-on experience with Microsoft Copilot Studio, covering both building agents and delivering training on the platform.</li><li>Practical Copilot Studio depth: topics and trigger design, generative answers and knowledge sources, actions and connectors, agent flows, publishing across channels (Teams, web, M365 Copilot), and testing and troubleshooting agents.</li><li>Demonstrated experience designing and delivering technical training to large organisations — instructor-led workshops, hands-on labs, train-the-trainer and champion programmes, for both business and technical audiences.</li><li>Working knowledge of the wider Microsoft AI stack: Azure AI Foundry / Azure OpenAI Service, Azure AI Search for retrieval, and how these complement low-code agents.</li><li>Familiarity with agent frameworks and protocols — Semantic Kernel, AutoGen, LangChain/LangGraph, MCP or similar — sufficient to position and compare approaches credibly.</li><li>Understanding of prompt and instruction design, RAG patterns, and agent evaluation — groundedness, task success, regression testing and quality measurement.</li><li>Understanding of Responsible AI in practice: content safety and filtering, guardrails, data boundaries, auditability and human oversight.</li><li>Working knowledge of the Power Platform (Power Automate, Dataverse) and of Microsoft 365 data sources as grounding and action surfaces for agents.</li><li>Comfort with code — Python or C#, plus REST APIs and integration patterns — enough to build custom actions, explain pro-code extensions and debug integrations.</li><li>Strong facilitation and communication skills, with the confidence to hold a room of senior stakeholders as well as a lab of hands-on makers.</li><li>Ability to produce enablement collateral independently — decks, lab guides, quick-reference material and recorded walkthroughs.</li></ul><br /><h2><b>Preferred / Good to Have</b></h2><br /><ul><li>Microsoft certifications: Azure AI Engineer Associate (AI-102), Power Platform Fundamentals (PL-900) or Developer (PL-400), or Copilot/agent-related Microsoft credentials.</li><li>Experience with declarative agents, the Microsoft 365 Agents Toolkit, Graph connectors or custom engine agents for deeper extensibility scenarios.</li><li>Experience taking agents to production — observability, cost and latency optimisation, versioning and lifecycle management.</li><li>Exposure to non-Microsoft agent platforms (AWS Bedrock Agents, Google Vertex AI Agents, open-source frameworks) for comparative positioning.</li><li>Experience across multiple industry domains (manufacturing, BFSI, consumer goods, energy, healthcare, or others).</li><li>Experience in a global delivery / SI environment (Avanade, Accenture, or similar) working with distributed teams across geographies.</li><li>Prior contribution to reusable training assets, agent accelerators or practice-building initiatives.</li></ul>