AI Lead / AI Solutions Architect

KPMG is one of the world’s leading professional services firms and the fastest growing Big Four accounting firm

About The Job:

• We are seeking an experienced AI Lead / AI Solutions Architect to drive the design, development, and deployment of enterprise-grade AI and Generative AI solutions.
• The ideal candidate will possess deep expertise in Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Cloud Technologies, and AI Product Lifecycle Management.
• This role requires a blend of technical leadership, solution architecture, stakeholder management, and business consulting capabilities to transform AI use cases into scalable production solutions that deliver measurable business outcomes.
• Experience: 12+ Years

Essential Job Functions:
AI Strategy & Solution Architecture

• Define and execute enterprise AI and Generative AI strategy aligned with business goals.
• Architect end-to-end AI solutions leveraging Machine Learning, Generative AI, Agentic AI, and Advanced Analytics.
• Evaluate business opportunities and identify high-value AI use cases.
• Develop scalable, secure, and production-ready AI architectures.
• Establish AI governance, evaluation frameworks, and model performance standards.

Generative AI & Agentic AI

• Design and implement solutions using:
  • Large Language Models (LLMs)
  • Retrieval Augmented Generation (RAG)
  • Multi-Agent Frameworks
  • AI Assistants and Copilots
  • Autonomous and Agentic Workflows
• Lead implementation of enterprise knowledge management and conversational AI platforms.
• Develop AI-powered automation solutions to improve operational efficiency and reduce manual effort.

AI Product Development

• Own the complete AI Product Lifecycle including:
  • Ideation
  • Business Case Development
  • Proof of Concept (PoC)
  • Minimum Viable Product (MVP)
  • Production Deployment
  • Scale and Adoption
• Create Product Requirement Documents (PRDs) and solution blueprints.
• Drive AI product roadmap, prioritization, and go-to-market strategy.
• Ensure business alignment and measurable ROI from AI investments.

Data Science & Advanced Analytics

• Lead development of:
  • Predictive Models
  • Demand Forecasting Solutions
  • Customer Lifetime Value (CLTV) Models
  • Customer Segmentation Frameworks
  • Recommendation Engines
  • Churn Prediction Models
  • Pricing Optimization Solutions
• Establish experimentation frameworks and A/B testing methodologies.
• Drive data-driven decision making using advanced analytics and AI insights.

Stakeholder & Program Leadership

• Act as the primary AI advisor for business and technology stakeholders.
• Lead cross-functional teams including Data Scientists, ML Engineers, Product Managers, and Business Teams.
• Manage multiple AI initiatives and portfolio delivery through structured governance models.
• Present AI strategy, architecture decisions, and business outcomes to leadership and executive stakeholders.

Delivery & Operations

• Drive AI platform implementation from pilot to enterprise-wide adoption.
• Establish MLOps and LLMOps best practices.
• Define monitoring, observability, model evaluation, and continuous improvement frameworks.
• Ensure compliance with security, privacy, and responsible AI standards.

Qualifications:
Required Skills & Experience

• 12+ years of overall IT experience.
• 6+ years of experience in Data Science, AI/ML, and Analytics.
• 3+ years of hands-on experience in Generative AI and LLM-based solutions.
• Proven experience leading enterprise AI transformation programs.
• Strong consulting and stakeholder management experience.

Technical Skills

Artificial Intelligence & Generative AI

• Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.).
• Retrieval Augmented Generation (RAG).
• Prompt Engineering.
• Fine-Tuning Strategies.
• Agentic AI and Multi-Agent Systems.
• Conversational AI.
• AI Evaluation Frameworks.

Machine Learning & Data Science

• Supervised and Unsupervised Learning.
• Forecasting.
• Recommendation Systems.
• Customer Analytics.
• Churn Models.
• Customer Lifetime Value (CLTV) Modeling.
• Marketing Mix Modeling (MMM).
• XGBoost and Advanced Machine Learning Algorithms.

Data & Engineering

• Python.
• SQL.
• PySpark.
• Databricks.
• Vector Databases.
• Data Pipelines.
• Feature Engineering.
• Data Architecture.

Cloud Platforms

• Microsoft Azure (Preferred).
• Azure AI Services.
• Azure OpenAI.
• Azure Machine Learning.
• AWS.
• Google Cloud Platform (GCP).

AI Operations

• MLOps.
• LLMOps.
• CI/CD for AI Systems.
• Model Monitoring.
• Responsible AI Practices.

Preferred Qualifications

• MBA or Master’s Degree in Analytics, Data Science, Computer Science, Artificial Intelligence, or a related field.
• Certifications in Azure AI, Data Science, Machine Learning, or Cloud Architecture.
• Experience working on enterprise AI programs across Retail, Telecom, Travel, Consumer Goods, or Digital businesses.
• Experience building AI Centers of Excellence (CoE) or AI Program Management Offices (PMOs).

Leadership Competencies

• Strategic Thinking.
• Executive Communication.
• Solution Consulting.
• Business Acumen.
• Innovation Mindset.
• Program Governance.
• Team Leadership.
• Stakeholder Management.
• Problem Solving.
• Customer-Facing Communication.

Success Metrics

• AI solution adoption and measurable business impact.
• Success and scalability of Generative AI implementations.
• Reduction in operational effort through AI-driven automation.
• Revenue growth and efficiency improvements delivered by AI initiatives.
• Timely delivery of AI products from concept to production.
• Stakeholder satisfaction and business value realization.