Associate Director, GenAI & Agentic AI Lead, Commercial Excellence COE – Global Capability Center

Key Responsibilities

Product Development & Innovation (Agentic AI for Commercial Excellence)

• Lead the design and development of agentic AI workflows across key Commercial Excellence levers (pricing, churn, revenue analytics, salesforce effectiveness)
• Translate business problems into AI-enabled solution architectures, including: Multi-agent systems for decisioning (e.g., pricing recommendations, churn interventions); LLM-powered insight generation and narrative synthesis; Conversational AI interfaces for tools (e.g., chatbot-driven analytics navigation)
• Build and scale modular, reusable AI accelerators and assets (e.g., Commercial Excellence AI modules, insight engines, recommendation agents)
• Define product roadmap for the AI-enabled Commercial Excellence platform, including integration with enterprise systems (ERP, CRM, data lakes)
• Partner with engineering teams to ensure scalable, production-grade deployment architectures (APIs, microservices, cloud platforms)
• Continuously optimize systems for performance, scalability, latency, and cost efficiency

Generative AI & Agentic Systems

• Architect and govern scalable, reusable agentic AI frameworks for enterprise use cases
• Define orchestration and execution patterns for multi-agent systems (event-driven workflows, planning/reflection loops)
• Develop reusable agent templates, blueprints, and context frameworks to accelerate deployment across Commercial Excellence use cases
• Evaluate solution design trade-offs across business value, data readiness, model performance, and cost
• Drive the development of PoCs, MVPs, and production-grade solutions, ensuring smooth transition from experimentation to scaled deployment
• Determine optimal use of LLMs vs traditional ML / rules-based approaches based on use case requirements

Client delivery and solution deployment

• Lead end-to-end delivery of AI-enabled Commercial Excellence engagements, including: Problem structuring and solution design, Model/agent development and deployment, Insight generation and executive storytelling
• Act as a bridge between technical AI teams and commercial stakeholders, ensuring business relevance and adoption
• Deploy agentic AI solutions in production environments, ensuring robustness, explainability, and usability
• Guide teams in integrating AI outputs into client decision-making workflows (pricing actions, churn interventions, sales plays)
• Communicate complex AI concepts effectively to both technical and non-technical stakeholders, including senior client leadership

Model Lifecycle, Quality, Cost & Risk Management

• Establish and govern MLOps / LLMOps frameworks, including model development, deployment, monitoring, and iteration
• Define and implement CI/CD pipelines, evaluation frameworks, and retraining workflows
• Optimize key components such as retrieval strategies, embeddings, prompting, grounding, and caching
• Drive improvements in model accuracy, relevance, latency, and cost efficiency, while minimizing hallucinations
• Implement frameworks for model evaluation, explainability, and robustness
• Ensure adherence to Responsible AI principles, including bias mitigation, privacy, security, and regulatory compliance

Business Development & Go-to-Market

• Co-create and lead client demos, POVs, and pilot programs showcasing agentic AI capabilities in Commercial Excellence
• Support proposal development and contribute to AI-led Commercial Excellence deal origination
• Build thought leadership around AI in Commercial Excellence (e.g., pricing AI, churn AI, sales AI)
• Partner with onshore leadership to position GCC as a core enabler of AI-led transformation

Capability building and team leadership

• Define best practices, frameworks, and playbooks for agentic AI development in Commercial Excellence
• Drive internal capability building across:
• Agentic AI frameworks, LLM application design, AI-driven analytics and decisioning
• Act as a thought leader within the GCC, shaping the evolution of AI capabilities across the Commercial Excellence practice

Qualification & Requirements

• 11-14 Years of experience
• Experience in consulting, analytics, AI/ML, or product-led environments, ideally with exposure to Commercial Excellence / Revenue Growth / Pricing domains
• Proven experience building and deploying Generative AI and Agentic AI solutions in real-world applications
• Strong understanding of Agentic AI frameworks (e.g., LangChain, CrewAI, AutoGen, or equivalent)
• Experience developing LLM-based applications, including: Retrieval-Augmented Generation (RAG), Insight generation and summarization, Conversational interfaces
• Proficiency in Python, SQL, and ML/AI libraries (e.g., Pandas, Scikit-learn, PyTorch)
• Experience with API development (FastAPI/Flask) and deploying solutions on cloud platforms (Azure, AWS, or GCP)
• Understanding of multi-agent orchestration, tool usage, memory, and planning paradigms
• Familiarity with data pipelines, model deployment, and productizing considerations
• Strong understanding of MLOps / LLMOps, APIs, and cloud-native architectures
• Experience with foundational models and APIs (e.g., OpenAI, Anthropic Claude, Google Vertex AI, Amazon Bedrock)
• Proven experience delivering AI-powered SaaS or internal platforms to automate workflows and enhance customer experience
• Strong business acumen with the ability to align AI strategy with enterprise goals
• Excellent problem-solving, communication, and leadership skills, with adaptability to the rapidly evolving AI landscape
• Strong understanding of Commercial Excellence concepts, including, but not limited to: Pricing and margin optimization, Customer segmentation and churn, Revenue analytics and growth strategy, Salesforce effectiveness
• Ability to translate business problems into AI-driven solutions
• Experience in data-driven problem solving and executive storytelling
• Experience working with senior stakeholders to shape commercial strategy and drive adoption, including leading workshops, influencing decision-making, and aligning cross-functional teams (sales, finance, product)
• Ability to develop clear, compelling executive storylines, distilling complex analyses and AI outputs into concise recommendations for C-suite audience
• Strong ability to engage with senior stakeholders and clients, including C-suite
• Demonstrated experience in leading teams and managing complex workstreams
• Ability to operate in ambiguous, fast-evolving environments and drive outcomes independently
• Entrepreneurial mindset with a focus on building scalable solutions and capabilities

Benefits

No information available.