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,

Positive 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.

📌 AADC-Industry & Functions-AI & Data-FS Insurance-Senior Manager (Gurugram)
🏢 Accenture services
📍 Gurugram