Job Summary

Title: AI/GenAI Manager

Educational qualification: BTech/Masters/PhD The Opportunity

We are seeking an experienced GenAI Manager with 10+ years of overall experience, including significant hands-on expertise in Generative AI, Agentic AI, RAG architectures, Conversational AI, and enterprise AI platforms. The ideal candidate will lead the design, delivery, governance, and scaling of AI solutions while managing cross-functional teams of AI engineers, data scientists, architects, and business stakeholders.

The role requires a strong blend of technical leadership, solution architecture, AI strategy, delivery management, and stakeholder engagement to drive enterprise-wide adoption of GenAI capabilities. The candidate should have proven experience delivering AI-powered solutions such as RAG applications, AI agents, copilots, knowledge management platforms, AI automation workflows, and multi-agent systems, while ensuring Responsible AI, quality, security, and scalability standards are met.

The individual will lead AI quality, validation, and governance initiatives to ensure the reliability, security, performance, and scalability of enterprise AI and GenAI solutions while partnering with technical and business teams.

Important: Hands-on experience delivering AI solutions in enterprise or production environments is required. Certifications, personal projects, and demos alone are not sufficient.

Application Guidance: Candidates should be able to explain at least two AI/GenAI implementations, including the business use case, their contribution, technical approach, and measurable outcomes.

Your key responsibilities

- Lead the design, development, and delivery of enterprise AI, GenAI, Agentic AI, and RAG-based solutions aligned with business objectives.
- Define AI strategy, roadmaps, governance frameworks, and operating models to enable scalable AI adoption across the organization.
- Drive the architecture and implementation of AI platforms, copilots, multi-agent systems, conversational AI solutions, and intelligent automation initiatives.
- Collaborate with business stakeholders to identify high-value AI use cases,



establish success metrics, and realize business value.
- Oversee the end-to-end AI solution lifecycle, including ideation, architecture, development, deployment, monitoring, and continuous improvement.
- Lead and mentor cross-functional teams of AI engineers, data scientists, architects, and developers, fostering innovation and delivery excellence.
- Establish best practices for Responsible AI, security, privacy, compliance, and risk management across AI implementations.
- Drive adoption of enterprise AI capabilities leveraging Azure AI Foundry, OpenAI, Databricks, vector databases, and contemporary AI frameworks.
- Ensure AI solutions are scalable, reliable, secure, and aligned with enterprise architecture and governance standards.
- Partner with engineering and business teams to define evaluation frameworks, quality standards, and performance metrics for AI systems.
- Guide the implementation of RAG architectures, knowledge management solutions, and agentic workflows to enhance business productivity and decision-making.
- Manage stakeholder communication, executive reporting, budgeting, resource planning, and delivery governance for AI programs.
- Stay current with emerging trends in GenAI, Agentic AI, multimodal AI, AI agents, and enterprise AI platforms to drive innovation and competitive advantage.
- Contribute to capability building, reusable accelerators, reference architectures, and thought leadership across the AI practice.

Skills and Attributes Professional Experience
- 10+ years of overall experience, including 5+ years leading AI/ML, GenAI, or data-driven transformation initiatives in enterprise environments.
- Proven experience delivering and scaling production-grade AI, GenAI, Agentic AI, Copilot,



and RAG-based solutions from concept through deployment and adoption.
- Strong understanding of enterprise AI architecture and hands-on exposure to multiple areas, including:
- LLM and GenAI application development
- RAG architectures and knowledge management solutions
- Agentic AI and multi-agent systems
- Conversational AI and Copilot solutions
- AI evaluation, governance, and Responsible AI
- AI platform engineering and cloud-based deployments
- MLOps / LLMOps and operationalization of AI solutions
- Data engineering, vector databases, and retrieval pipelines

- Demonstrated ability to lead cross-functional teams of AI engineers, architects, data scientists, and developers.
- Strong stakeholder management skills with experience translating business needs into scalable AI solutions and measurable business outcomes.
- Experience with enterprise AI platforms such as Azure AI Foundry, OpenAI, Databricks, Microsoft Copilot, and related AI ecosystems.

Educational Background
- Bachelors/masters degree in computer science, Data Science, Engineering, or related field.

Technical Skills
- Strong understanding of Large Language Models (LLMs), Generative AI, Agentic AI, Multi-Agent Systems, and RAG architectures.
- Proven experience designing and delivering enterprise-scale GenAI, Copilot, Conversational AI, and AI Agent solutions.
- Experience defining AI strategy, solution roadmaps, architecture standards, and operating models.
- Strong knowledge of AI platform ecosystems including Azure AI Foundry, Azure OpenAI, Databricks, Vector Databases, and Enterprise Search platforms.
- Experience leading the design and implementation of RAG pipelines, knowledge management solutions, and AI-powered business applications.
- Understanding of AI evaluation, guardrails, observability, quality metrics, and Responsible AI practices.
- Experience establishing governance frameworks covering AI security, privacy, compliance, safety, and risk management.
- Strong knowledge of prompt engineering, agent orchestration frameworks, tool integrations, and workflow automation.

📌 EY - GDS Consulting - AIA- Full stack engineer - Manager (Kolkata)
🏢 EY
📍 Kolkata