Manager - Service Delivery Automation

Position Description:

Key Responsibilities:

• Design and prototype novel agentic workflows that integrate LLMs with enterprise systems (CRMs, ERPs, APIs) and data sources.
• Serve as the organization's subject matter expert on Generative AI, LLMs, and agentic architectures, providing guidance to RPA, BI, and Data Analytics teams.
• Develop a strategic roadmap for integrating LLMs across the service delivery automation portfolio.
• Lead proof-of-concept projects to demonstrate the business value of AI agents in automating complex, cognitive tasks.
• Collaborate with clients to drive digital transformation and identify opportunities for engagement.
• Serve as the primary liaison between clients and offshore teams, ensuring seamless communication and alignment.
• Lead a team of Developers, Business Analysts, and Data Scientists to infuse advanced AI capabilities into projects and build revenue-generating AI products..
• Oversee the full project lifecycle, ensuring timely, high-quality delivery and thorough feasibility assessments.
• Support solution design and estimation, ensuring alignment with client needs and expectations.
• Identify and propose innovative solutions using RPA, AI, data science, and business intelligence.

Technical Qualifications:

• Expertise in Agentic AI & LLMs:
• Deep, hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
• Proven ability to design, develop, and deploy autonomous and semi-autonomous AI agents and workflows.
• Expertise in prompt engineering, model fine-tuning, and Retrieval-Augmented Generation (RAG) architectures.
• Proficiency with vector databases (e.g., Pinecone, ChromaDB, Weaviate) and their integration.
• Experience with major LLM APIs (e.g., OpenAI, Google Gemini, Anthropic) and open-source models.
• Experience with RPA tools (e.g., UiPath, PowerAutomate) as platforms for deploying AI agents..
• Proficiency in Python is a must along with VBA, JavaScript, C#, and database architecture.
• Strong background in AI, machine learning, and data science (predictive analytics, data modeling).