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 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
o Oversee the end-to-end lifecycle of AI projects, from requirements gathering and solution architecture to deployment and post-implementation support
o Provide thought leadership and guidance to consultants and engineers on cutting-edge Gen AI and Agentic AI technologies
o Define and communicate a strategic vision for AI agent solutions, ensuring alignment with client business objectives
Client & Stakeholder Engagement
o Act as a trusted advisor to clients, translating complex AI concepts into actionable business solutions
o Drive discussions on Gen AI best practices, risk management, AI safety, and governance
- Advanced Generative AI & Agentic System Development
o Design and implement sophisticated AI agents using frameworks like AI Refinery, LangChain, AutoGen, CrewAI, and custom agentic architectures
o Develop multi-agent systems that can collaborate, negotiate, and execute complex workflows autonomously
o Implement Model Context Protocol (MCP) integrations for seamless communication between AI systems and external tools/APIs
o Build and deploy Generative AI applications with advanced reasoning, planning, and execution capabilities
- Leverage Advanced Data Science Techniques:
o Develop solutions using Computer Vision, Machine Learning, and Large Language Models (LLMs).
o Define data requirements, clean, aggregate, analyze, and interpret data while conducting data quality assessments.
- Develop and Implement AI Models:
o Build and deploy AI models and Generative AI applications.
o Train and fine-tune LLMs using large-scale datasets to optimize performance and accuracy.
o Evaluate model performance and implement iterative improvements.
- Solution Integration and Deployment:
o Collaborate to integrate AI solutions into end-to-end workflows, ensuring scalability.
o Utilize cloud platforms like AWS, Azure, or GCP for model development and deployment.
- Innovation and Knowledge Sharing:
o Stay updated on advancements in AI and Data Science, exploring innovative techniques and frameworks.
o Document methodologies and findings for effective knowledge sharing.
Professional & Technical Skills:
- Must To Have Skills: Expert proficiency in Generative AI, Agentic AI Systems, Model Context Protocol (MCP), LLMs, Multi-Agent Systems, Python, SQL, AI Agent Orchestration frameworks.
- Cloud & Infrastructure: AWS/Azure/GCP, Docker, Kubernetes, Spark, MLOps pipelines for agentic systems
- Specialized Knowledge: NLP, Computer Vision, Reinforcement Learning for agent training, Multi-modal AI systems
- Experience in developing and AI/ML models.
The ideal candidate will possess deep expertise in agentic AI systems with a proven track record of building autonomous AI solutions that can execute complex business workflows
- Strong understanding of AI safety, alignment, and governance principles for autonomous systems
- Experience with enterprise-grade AI agent deployments and production system management
- This position is based at our Gurugram office with opportunities to lead cutting-edge AI innovation projects
About Our Company | Accenture
Experience
: Minimum 7 years of experience in AI/ML, with demonstrated expertise leading teams in Generative AI application and agentic system delivery, preferably within a consulting or client-facing environment
Educational Qualification
: Bachelor's or Master's degree (BE/BTech/MBA/MS) in Statistics, Computer Science, Mathematics, AI/ML, or related disciplines with an excellent academic record
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