Highlights:
5.00 – 9.00 Years
15.00 – 28.00 INR (Lacs)/Yearly
Full-time
Bengaluru
Skills
Agentic Ai
ai strategy
Data Products
Roles & Responsibility
Practice: Technology Strategy & Transformation, Global Network
Areas of Work: GenAI Strategy & Architecture
Level: Consultant
Location: Bangalore / Gurugram / Mumbai / Pune / Chennai / Kolkata / Hyderabad
Years of Experience: 5 to 9 years
Bring Your Best Skills Forward to Excel in the Role
- Process Hotspot Identification: Identify high-value business processes where Agentic AI can eliminate friction and unlock measurable value, using process analysis, business process mapping, process mining, and value-led prioritisation frameworks across target industries.
- Agentic AI Design & Architecture: Design agentic workflows, multi-agent orchestration, and AI agent architecture for production deployment. Demonstrate deep expertise in LLM architecture, prompt engineering, GenAI platforms, and framework selection (LangChain, AutoGen, CrewAI, or equivalent).
- Enterprise AI & GenAI Strategy: Design & guide development of enterprise-wide AI & GenAI strategy for clients. Leverage strong expertise and certification in cloud AI platforms — Google Vertex AI / Gemini, Azure AI / Copilot, Claude, Amazon Bedrock, IBM Watson — as well as open-source models.
- Scaled AI Deployment & MLOps: Guide implementation from advisory and prototype through to production-grade, scaled AI deployment, covering AI productionisation, MLOps, AI governance, model monitoring, change management, and value realisation frameworks.
- Responsible AI & Governance: Have a deep understanding of Responsible AI & GenAI frameworks, including bias detection, explainability, fairness, and regulatory compliance, to engage clients in meaningful discussions and steer towards the right recommendations.
- Business Case & Value Realization: Define an AI use case driven value realization framework and build quantitative and qualitative business cases relevant to the client’s industry. Benchmark against global research and leading industry peers.
- Proof of Concepts & Prototyping: Help design and lead POCs and high-level solutions using AI or GenAI analytics to derive insights from data. Collaborate with business experts, platform engineers, and technology teams for prototyping and client implementations.
- Discovery Workshops & Stakeholder Engagement: Conduct discovery workshops and design sessions to elicit AI & GenAI opportunities and client pain areas. Use advanced presentation, public speaking, and content creation skills for C-level discussions.
- Solution Architecture & Technology Landscape: Assess impact to client’s technology landscape/architecture; formulate guiding principles and platform components. Demonstrate knowledge of IT & enterprise architecture concepts — Cloud, API-first, MCP, agent orchestration, RAG, observability.
- Budgeting & Financial Proposals: Manage budgeting and forecasting activities and build financial proposals for AI transformation engagements.
Requirements
Your Experience Counts!
- MBA from a tier 1 institute preferred.
- 3 – 5 years of Strategy Consulting experience at a consulting firm.
- 2+ years of experience in designing and building end-to-end Enterprise AI and GenAI strategic solutions using cloud and non-cloud platforms — Google Vertex AI / Gemini, Azure AI / Copilot, Claude, Amazon Bedrock, IBM Watson, DataRobot, or equivalent.
- Excellent understanding of Traditional AI, Generative AI, Agentic AI, multi-agent orchestration, and Advanced Cognitive methods to derive insights and actions.
- Demonstrated ability to design agentic AI workflows, including LLM architecture, prompt engineering, workflow automation, and AI agent design for production environments.
- 2+ years of experience writing business cases (quantitative and qualitative) to support strategic business initiatives or AI & Data transformation, including value realisation and AI governance frameworks.
- Good working knowledge in formulation of relevant guiding principles and platform components with expertise in Responsible AI frameworks, including bias, explainability, and regulatory compliance.
- 2+ years of experience leading or managing large teams effectively including planning/structuring analytical work, facilitating team workshops, and developing AI strategy recommendations as well as developing POCs.
- Deep understanding of data supply chain and how it enables AI productionisation and scaled deployment.
- Mandatory knowledge of IT & Enterprise architecture concepts through practical experience — Cloud, API-first, RAG, MCP, agent orchestration, MLOps, observability.
- Strong understanding in any of the following industries preferred: Financial Services, Retail, Consumer Goods, Telecom, Life Sciences, Transportation, Automotive/Industrial, or equivalent.
- Cloud AI Practitioner Certifications (Azure, AWS, Google) desirable but not essential.
