AADC-Industry & Functions-AI & Data-FS Insurance-Senior Manager

Job Description

Entity: - Accenture AI & Data

Practice: - FS - Insurance

Title: - Ind & Func AI Decision Science Sr. Manager

Job location: - Gurugram, Bengaluru

Management Level : 6 – Senior Manager

Location: Open

Must have skills: Generative AI, Agentic AI, Model Context Protocol (MCP), Large Language Models (LLMs), Multi-Agent Systems, Python, SQL, AI Agent Orchestration, Machine Learning,

Good to have skills: AI Refinery, LangChain, LlamaIndex, AutoGen, Crew AI, Spark, Cloud Platforms (AWS, Azure, GCP), NLP, Computer Vision, Vector Databases, RAG (Retrieval-Augmented Generation), Function Calling, Tool Integration

Job Summary: As an AI Decision Science Sr. Manager, you will lead cross-functional teams in the design, development, and deployment of advanced AI agents and multi-modal AI solutions that autonomously execute complex business workflows. You will be responsible for defining and implementing Gen AI and agentic AI strategies for clients, ensuring successful delivery of large-scale AI initiatives. Your expertise will drive innovation, build client relationships, and shape the roadmap for autonomous AI-driven business transformation. Roles & Responsibilities:

– Strategic Leadership & Project Delivery

• Oversee the end-to-end lifecycle of AI projects, from requirements gathering and solution architecture to deployment and post-implementation support
• Provide thought leadership and guidance to consultants and engineers on cutting-edge Gen AI and Agentic AI technologies
• Define and communicate a strategic vision for AI agent solutions, ensuring alignment with client business objectives
• Client & Stakeholder Engagement
• Act as a trusted advisor to clients, translating complex AI concepts into actionable business solutions
• Drive discussions on Gen AI best practices, risk management, AI safety, and governance
  
  

– Advanced Generative AI & Agentic System Development

• Design and implement sophisticated AI agents using frameworks like AI Refinery, LangChain, AutoGen, CrewAI, and custom agentic architectures
• Develop multi-agent systems that can collaborate, negotiate, and execute complex workflows autonomously
• Implement Model Context Protocol (MCP) integrations for seamless communication between AI systems and external tools/APIs
• Build and deploy Generative AI applications with advanced reasoning, planning, and execution capabilities
  
  

– Leverage Advanced Data Science Techniques:

• Develop solutions using Computer Vision, Machine Learning, and Large Language Models (LLMs).
• Define data requirements, clean, aggregate, analyze, and interpret data while conducting data quality assessments.
  
  

– Develop and Implement AI Models:

• Build and deploy AI models and Generative AI applications.
• Train and fine-tune LLMs using large-scale datasets to optimize performance and accuracy.
• Evaluate model performance and implement iterative improvements.
  
  

– Solution Integration and Deployment:

• Collaborate to integrate AI solutions into end-to-end workflows, ensuring scalability.
• Utilize cloud platforms like AWS, Azure, or GCP for model development and deployment.
  
  

– Innovation and Knowledge Sharing:

• Stay updated on advancements in AI and Data Science, exploring innovative techniques and frameworks.
• Document methodologies and findings for effective knowledge sharing.