AI Architect
Zensar
AI Architect
Zensar
Global IT services for digital transformation
AI Architect
Experience: 12–16 Years
Location: Pune / Bengaluru / Hyderabad
Looking for a workplace where people realize their full potential, are recognized for the impact they make, and enjoy the company of the peers they work with? Welcome to Zensar! Read on for more details on the role and about us.
We are seeking an experienced AI Architect to lead the design and implementation of enterprise-scale AI, Generative AI, and Agentic AI solutions. The ideal candidate will be responsible for defining AI architecture strategy, designing scalable AI platforms, and driving the adoption of intelligent solutions that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents.
The role requires close collaboration with business stakeholders, AI engineers, data scientists, and delivery teams to transform business challenges into practical AI solutions. The candidate should possess expertise in architecting GenAI applications, conversational AI, knowledge assistants, agent-based workflows, and AI governance frameworks while ensuring scalability, security, and responsible AI adoption.
Required Skills
10+ years of overall IT experience with significant experience in AI/ML solution architecture.
Strong expertise in designing and implementing Generative AI, Machine Learning, and Agentic AI solutions.
Hands-on experience with Large Language Models (LLMs) such as GPT, Gemini, Claude, Llama, or similar foundation models.
Experience architecting RAG (Retrieval-Augmented Generation) solutions using vector databases and enterprise knowledge repositories.
Strong understanding of Agentic AI architectures, AI Assistants, AI Copilots, and multi-step orchestration workflows.
Experience with AI application frameworks such as LangChain, LangGraph or similar Agentic AI frameworks.
Expertise in Prompt Engineering, AI workflow design and LLM application architecture.
Strong knowledge of AI evaluation, observability, governance, and responsible AI practices.
Experience with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, or Scikit-Learn.
Experience leveraging cloud-based AI services on Azure, AWS, or Google Cloud Platform.
Understanding of vector databases, semantic search, embeddings, and enterprise knowledge management solutions.
Experience integrating AI solutions with enterprise applications, APIs, and business workflows.
Strong customer engagement, solutioning, architecture review, and stakeholder management skills.
Ability to provide technical leadership and mentor AI engineering teams.
The role requires close collaboration with business stakeholders, AI engineers, data scientists, and delivery teams to transform business challenges into practical AI solutions. The candidate should possess expertise in architecting GenAI applications, conversational AI, knowledge assistants, agent-based workflows, and AI governance frameworks while ensuring scalability, security, and responsible AI adoption.
Required Skills
10+ years of overall IT experience with significant experience in AI/ML solution architecture.
Strong expertise in designing and implementing Generative AI, Machine Learning, and Agentic AI solutions.
Hands-on experience with Large Language Models (LLMs) such as GPT, Gemini, Claude, Llama, or similar foundation models.
Experience architecting RAG (Retrieval-Augmented Generation) solutions using vector databases and enterprise knowledge repositories.
Strong understanding of Agentic AI architectures, AI Assistants, AI Copilots, and multi-step orchestration workflows.
Experience with AI application frameworks such as LangChain, LangGraph or similar Agentic AI frameworks.
Expertise in Prompt Engineering, AI workflow design and LLM application architecture.
Strong knowledge of AI evaluation, observability, governance, and responsible AI practices.
Experience with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, or Scikit-Learn.
Experience leveraging cloud-based AI services on Azure, AWS, or Google Cloud Platform.
Understanding of vector databases, semantic search, embeddings, and enterprise knowledge management solutions.
Experience integrating AI solutions with enterprise applications, APIs, and business workflows.
Strong customer engagement, solutioning, architecture review, and stakeholder management skills.
Ability to provide technical leadership and mentor AI engineering teams.
Digital solutions and IT services company that partners with global organizations to drive digital transformation. Its offerings include intelligent automation, analytics, hyperconverged infrastructure, and digital application development and maintenance, delivered through long-term contracts, project-based engagements, and managed services. Indigo Slate handles virtual event creation. Zensar’s Living AI integrates artificial intelligence into business processes to boost outcomes. Unlike many competitors, it emphasizes reducing capital expenditure (Capex) and operating expenditure (Opex), simplifying vendor management, and improving efficiency through automation. The overall goal is to help clients adapt to the digital landscape, optimize technology infrastructure, and achieve higher operational efficiency.
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