Gen AI Lead

Zensar seeks a Gen AI Lead to set the strategy, design the architecture, and oversee development and production deployment of enterprise-grade generative AI solutions. The role leads AI engineers, data scientists, application developers, and solution architects. The posting lists a Hyderabad office address and states “Work from Anywhere: Yes.”

Responsibilities

• Define the generative AI roadmap with business leaders, prioritize use cases, measure business value, and establish governance, security, compliance, and Responsible AI practices.
• Design scalable solutions using large language models, retrieval-augmented generation, multi-agent systems, copilots, and chatbots. Build reusable frameworks, accelerators, and architectural best practices.
• Lead delivery of AI assistants, enterprise copilots, knowledge-management and intelligent-document-processing solutions, code-generation tools, and business automation. Oversee model selection, prompting, evaluation, testing, and deployment; integrate solutions with SAP, Microsoft 365, CRM, ERP, ServiceNow, and other enterprise applications.
• Mentor engineers and architects, conduct technical reviews, guide proofs of concept and innovation activities, and develop organizational AI capabilities. Outcomes include successful delivery, adoption and business value, reduced operational effort, solution accuracy and reliability, team development, and governance compliance.

Qualifications and tools:

• A bachelor’s or master’s degree in Computer Science, AI, Data Science, Engineering, or a related field; 8–15 years of overall IT experience and 3+ years of hands-on AI/ML or generative AI experience. A separate job-information section lists minimum and maximum experience as 3 and 8 years. Python is mandatory. Leadership, stakeholder management, communication, analytical ability, and experience leading AI teams are sought.
• Required technical areas include LLMs, agentic AI, RAG, fine-tuning, model evaluation, function calling, tool integration, guardrails, and Responsible AI. Listed tools include LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, Azure AI Foundry, FastAPI, REST APIs, vector databases and search tools, cloud AI platforms, GitHub, Azure DevOps, Docker, Kubernetes, CI/CD, and MLflow.
• Preferred: enterprise GenAI program delivery, Azure OpenAI solutions, integration with SAP ECC/S4HANA, Microsoft 365, SharePoint, Teams, Salesforce, or ServiceNow; experience in healthcare, pharmaceutical, manufacturing, BFSI, or retail; managing distributed global teams; and Azure AI Engineer, Azure OpenAI, AWS AI/ML, or equivalent certifications. Microsoft Azure is the preferred cloud platform.