AI Architect Consultant

As part of this high-performing team, you will work on scaling AI and the data that fuels it to power every single person and every single process. You will design and guide enterprise-wide AI and GenAI solutions, from advisory through to production-grade deployment, working at the intersection of strategy and technology.

Responsibilities:

• Business Case and Value Transformation: Assessment of AI potential and development of use cases, including process hotspot identification using process mining and value-led prioritization that can transform business operations.
• Agentic AI Design: Help design agentic workflows, multi-agent orchestration, and AI agent architecture for production-grade deployment using LLMs and GenAI platforms.
• Formulation of Guiding Principles and Components: Assess impact on the client's technology landscape/architecture and ensure formulation of relevant guiding principles and platform components for AI solutions.
• Scaled AI Deployment: Evaluate options for AI productionization and scaled deployment, including MLOps, AI governance, value realization tracking, and change management.
• 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 prioritization frameworks across target industries.
• Agentic AI Design and 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 and GenAI Strategy: Design and guide the development of enterprise-wide AI and GenAI strategy for clients. Leverage strong expertise and certification in cloud AI platforms Google Vertex AI / Gemini, Azure AI / Copilot, Claude, Amazon Bedrock, and IBM Watson, as well as open-source models.
• Scaled AI Deployment and MLOps: Guide implementation from advisory and prototype through to production-grade, scaled AI deployment, covering AI productionization, MLOps, AI governance, model monitoring, change management, and value realization frameworks.
• Responsible AI and Governance: Have a deep understanding of Responsible AI and GenAI frameworks, including bias detection, explainability, fairness, and regulatory compliance, to engage clients in meaningful discussions and steer towards the right recommendations.
• Business Case and 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 and 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 and Stakeholder Engagement: Conduct discovery workshops and design sessions to elicit AI and GenAI opportunities and client pain areas. Use advanced presentation, public speaking, and content creation skills for C-level discussions.
• Solution Architecture and Technology Landscape: Assess impact on the client's technology landscape/architecture; formulate guiding principles and platform components. Demonstrate knowledge of IT and enterprise architecture concepts: cloud, API-first, MCP, agent orchestration, RAG, and observability.
• Budgeting and Financial Proposals: Manage budgeting and forecasting activities and build financial proposals for AI transformation engagements.

Requirements:

• 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 and data transformation, including value realization and AI governance frameworks.
• Good working knowledge of the 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 the data supply chain and how it enables AI productionization and scaled deployment.
• Mandatory knowledge of IT and enterprise architecture concepts through practical experience Cloud, API-first, RAG, MCP, agent orchestration, MLOps, and 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) are desirable but not essential.