Data Science Consultant

About the Role

As an AI Decision Science Analyst, you will lead the design, development, and deployment of sophisticated AI agents and multi-modal AI solutions that can autonomously execute complex business workflows. You will leverage cutting-edge Generative AI, Agentic AI frameworks, and Model Context Protocol (MCP) integrations to create intelligent systems that can reason, plan, and act independently to solve complex business challenges across various industries. Your expertise will drive innovation in autonomous AI solutions and deliver transformative value for clients through intelligent agent orchestration and seamless system integrations.

Key Responsibilities

• 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.

Requirements & Tech Stack

• Must-Have Skills:
• Expert proficiency in Generative AI, Agentic AI Systems, Model Context Protocol (MCP), Large Language Models (LLMs), Multi-Agent Systems, Python, SQL, AI Agent Orchestration frameworks.
• 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.
• 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:
• Experience in developing AI/ML models.
• 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.

Qualifications

• Location: Gurgaon