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S&C Global Network - AI - Data Strategy – Consultant

Accenture · Bengaluru, India

About this role

The S&C Global Network - AI - Data Strategy Consultant role at Accenture involves shaping client futures by combining deep business insight with AI and Generative AI strategy. You will work within the Engineering Products team to develop innovative AI strategies, value-driven use cases, and technological roadmaps for clients across industries like Lifesciences, CPG, Retail, and Hospitality. Responsibilities include designing and deploying custom Copilot solutions within the Microsoft 365 ecosystem, utilizing Copilot Studio for conversational AI, and integrating capabilities via REST APIs and Microsoft Graph. You will collaborate with stakeholders to translate business needs into technical specifications, build automation workflows, and ensure solutions meet enterprise security and governance standards. Required qualifications include a bachelor’s or master’s degree in a relevant field and at least 5 years of experience (as per the primary job listing header). Candidates must possess strong analytical skills, expertise in AI technologies including ML, NLP, and LLMs, and proficiency in Python or JavaScript/TypeScript. Experience with Azure AI services and the Microsoft Power Platform is essential. Desirable qualifications include experience in client-facing consultancy, familiarity with Agile methodologies, and relevant Microsoft certifications.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Microsoft Copilot StudioPower BIPower PlatformGenerative AIMicrosoft 365REST APIsMicrosoft Graph APIPower AutomatePythonJavaScriptTypeScriptAzure OpenAILarge Language Models (LLMs)Prompt EngineeringMachine LearningNatural Language Processing (NLP)Computer VisionDeep LearningCloud Computing

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Custom Copilot Development
Designing and deploying conversational AI agents within the Microsoft 365 ecosystem using Copilot Studio. This requires technical proficiency in integrating these agents with business platforms like Power BI, Teams, and SharePoint to automate workflows.
AI Strategy and Value Realization
Translating complex business needs into actionable AI roadmaps. You must bridge the gap between technical AI capabilities (LLMs, ML, NLP) and specific industry outcomes for sectors like Lifesciences, CPG, and Retail.
System Integration and Governance
Building robust integrations using REST APIs and Microsoft Graph while ensuring all AI solutions adhere to enterprise-grade security, data governance, and compliance standards.

Likely challenges to think through

Balancing Technical Depth with Stakeholder Communication
You will need to explain complex Generative AI concepts and technical specifications to non-technical business stakeholders. Prepare by practicing how to articulate the business value of an AI solution without relying on jargon.
Navigating Enterprise Security Constraints
Deploying AI solutions in large, regulated organizations often involves strict data privacy and security hurdles. Prepare by demonstrating your experience in designing solutions that respect data sovereignty and enterprise governance policies.
Rapid Evolution of the AI Ecosystem
The Microsoft Copilot and Azure AI landscape changes quickly. You must demonstrate a proactive approach to learning new features and adapting your development methods to keep solutions current and performant.

Practice your answers

Technical practice

Designing Custom Copilot Solutions

What to coverExplain your approach to designing a custom Copilot within the Microsoft 365 ecosystem. Focus on how you identify high-impact use cases, map them to specific M365 applications like Power BI or Teams, and ensure the solution aligns with enterprise security and governance standards.

Integrating AI with Microsoft Graph API

What to coverDescribe how you utilize the Microsoft Graph API to enhance Copilot functionality. Discuss the challenges of data retrieval and security when integrating external business systems with conversational AI agents.

LLM Selection and Strategy

What to coverWhen proposing an LLM for a client, what criteria do you use to evaluate suitability? Address factors such as model performance, cost, latency, and alignment with specific industry needs like Lifesciences or Retail.

Prompt Engineering Best Practices

What to coverHow do you approach prompt engineering to ensure consistent and accurate outputs from LLMs? Discuss techniques for handling context, managing system instructions, and mitigating hallucinations in a production environment.

Automation with Power Automate

What to coverProvide an example of how you have used Power Automate to extend the capabilities of an AI agent. Explain how you handle error logging, workflow triggers, and data transformation between disparate systems.

Azure AI Services Implementation

What to coverDetail your experience with Azure OpenAI services. Explain how you manage model deployment, fine-tuning, and monitoring to ensure the AI solution remains performant and compliant over time.

Data Architecture for AI

What to coverHow do you assess a client's existing data infrastructure to determine if it is ready for Generative AI integration? Discuss the importance of data quality, accessibility, and security in building a foundation for AI scaling.

REST API Integration

What to coverExplain your process for building custom connectors using REST APIs to bridge AI agents with legacy business applications. Focus on authentication methods, data mapping, and maintaining secure API communication.

Behavioural practice

Translating Technical Concepts for Stakeholders

What to coverDescribe a time you had to explain a complex AI strategy to a non-technical client. How did you ensure they understood the business value and the technical trade-offs involved?

Managing Conflicting Requirements

What to coverTell me about a situation where you had to balance a client's ambitious AI feature request with technical constraints or security limitations. How did you negotiate a solution that satisfied both parties?

Handling Project Ambiguity

What to coverDescribe a project where the initial requirements were unclear. What steps did you take to define the scope, gather necessary information, and align the team on a clear technical roadmap?

Collaborating in Agile Environments

What to coverProvide an example of how you have worked within an Agile team to deliver an AI solution. How did you manage your tasks, communicate progress, and adapt to changing priorities during the development lifecycle?

Sharpen your knowledge

Topics to prepare

Generative AI Strategy and Value Frameworks
Review how to align AI initiatives with business outcomes in industries like Lifesciences or Retail. Exercise: Draft a hypothetical AI roadmap for a retail client that identifies three high-impact use cases, focusing on how to measure ROI and business value, which is central to the S&C Global Network's consulting approach.
Enterprise AI Governance and Security
Understand the requirements for deploying AI solutions within a corporate environment. Exercise: Research Microsoft's enterprise-grade security standards for Copilot and Power Platform, then outline a checklist for ensuring data privacy and compliance when integrating LLMs with proprietary business data.

Skills to revise

Microsoft Copilot Studio and Power Platform Integration
Develop proficiency in building conversational agents and automation workflows. Exercise: Create a simple custom Copilot in Copilot Studio that connects to a data source via a REST API, and use Power Automate to trigger a specific business action based on the user's input.
Microsoft Graph API and REST API Integration
Master the ability to connect AI agents to the Microsoft 365 ecosystem. Exercise: Practice authenticating and retrieving data from Microsoft 365 services (like SharePoint or Outlook) using the Microsoft Graph API, ensuring you understand how to handle permissions and data scoping.
Prompt Engineering for LLMs
Refine the ability to optimize model outputs for business tasks. Exercise: Take a complex business process, such as summarizing meeting transcripts or extracting data from reports, and iterate on a system prompt to improve the accuracy and relevance of the LLM's response.

Your preparation checklist

Develop a Microsoft Copilot Studio project walkthrough
Prepare a demonstration of a custom conversational agent built in Copilot Studio. Ensure your walkthrough highlights how you integrated the agent with external data sources via REST APIs or Microsoft Graph, and explain how you handled enterprise security and governance requirements.
Map AI strategy to industry-specific business value
Create a brief case study or presentation outlining how you would apply Generative AI to a specific challenge in Lifesciences, CPG, or Retail. Focus on the end-to-end lifecycle, from problem definition and data preparation to model deployment and monitoring.
Demonstrate proficiency in Power Platform automation
Prepare a technical summary of a workflow you built using Power Automate to extend AI functionality. Be ready to explain how you used Python or TypeScript to handle complex logic or data transformations within the Microsoft 365 ecosystem.
Prepare for technical discussions on LLMs and Prompt Engineering
Review your experience with Azure OpenAI and various LLMs. Be prepared to discuss your methodology for prompt engineering, how you evaluate model performance, and how you select the most appropriate model for specific business use cases.
Formulate strategic questions for the interviewer
Prepare thoughtful questions regarding the team's approach to AI governance, how they balance rapid prototyping with enterprise-grade security, and how the Engineering Products team collaborates with clients to define long-term AI roadmaps.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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