Role intent Live

Consultant, AI Business Solutions

Microsoft

Work Mode

Onsite

Employment Type

FULL TIME

Location

India, Telangana, Hyderabad, India, Karnataka, Bangalore

Application Deadline

August 24, 2026

Apply configure‑before‑customize principles while contributing to delivery plans that consider AI capabilities, extensibility, data dependencies, and long‑term maintainability of Copilot and Power Platform solutions.

Responsibilities

Support innovation through the implementation of AI‑augmented features such as intelligent case handling, summarization, recommendations, conversational experiences, and Copilot‑driven productivity scenarios. Ensure solutions align with approved architecture and security guidelines, contributing to build specifications, testing activities, and operational documentation for AI‑enabled and Copilot solutions. Identify and escalate technical risks related to AI‑enabled solutions, including data access, security, compliance, performance, and solution reliability, working with senior team members on mitigation plans. Support deployment and stabilization of solutions, assisting with troubleshooting, configuration adjustments, and user adoption for Copilot and AI‑integrated workloads.

Required Qualifications

Bachelor's degree in computer science, Engineering, Business, or related field, or equivalent experience. Experience supporting full solution lifecycle: requirements, build, test, deployment, and post‑go‑live support Hands‑on implementation experience with Dynamics 365 Customer Engagement, Power Platform, M365 Copilot. Proven delivery of Dynamics 365 CE/Power Platform solutions, M365 Copilot Solutions, plus experience building AI-infused workflows (recommendations, summarization, case routing, contact center assist, sales/service copilots) with production-grade engineering practices. Experience with Agile delivery and DevOps practices Ability to identify technical risks before they occur and to develop mitigation and avoidance strategies Implements appropriate guardrails and evaluation practices to ensure GenAI solutions are reliable, grounded, secure, and cost-/performance-efficient, aligned with Responsible AI principles and enterprise standards. Produces high-quality documentation and reusable assets (design artifacts, configuration guides, operational runbooks) and enables customer and partner teams to independently support and evolve the solution after handoff

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